Five Key Advantages for CROs Utilizing Next-Gen Software and Digital Tools

The importance of Agriculture trial data reporting

Agriculture trial data reporting is a critical part of developing new crop protection, nutrition, crop varieties, and genetics. It’s no secret that developing new crop production chemistries is a challenging process for agribusiness companies.  

Agricultural trials remain essential in bridging the gap between pure scientific research and scale agriculture and ensuring the effectiveness of new products and technologies under real farming conditions. 

In recent years, however, the pace of innovation among the large agribusiness companies producing seed and crop protection products has slowed considerably due to increased costs of product development. 

Evaluations of new varieties, technologies, and products depend on data generated from trials. However, such multi-faceted variety evaluation is expensive and time-consuming. Thus, the use of these data needs to be optimized. 

Regulatory testing adhering to globally harmonized guidelines and best practices, plays a major role in the registration of the products. With the depth and spread of the ever-increasing regulatory expectations and the advent of new scientific tools, it has become more common for agribusiness companies to outsource product evaluations. The CRO business model has existed since the 1970s within crop protection after safety and efficacy regulations became more stringent for new crop protection products. 

This article explores the importance of field-scale agronomic trials and five transformative ways agriculture data analytics is proving invaluable for CROs in agriculture trial data reporting. 

Why are large-scale agronomic trials essential?

Knowing how a crop variety or product performs under local conditions is important. The current challenges in agricultural production are more likely to be addressed by locally adapted solutions that consider both environmental and socioeconomic information.  

For trials to be relevant they need to be conducted in a soil and climatic area that is representative of the reality of a crop grown on a farm. For example, a CRO in Spain will say that the outcome of a trial in the US is not necessarily relevant proof of the pudding for Spanish conditions. 

In addition, crop breeders need to evaluate the proposed genotypes against existing varieties in a country or region. 

During the long process of testing and evaluating new products, many factors can complicate the process. Client needs can change, new regulatory requirements emerge, and competitive products can pre-empt opportunities. Crop protection products are some of the most regulated in the world. This regulation ensures that while we protect our crops, we’re also safeguarding the environment and human health, ensuring a healthier planet for future generations–for good reason so the process requires thorough and repetitive testing. 

For example, new crop varieties need to meet multiple criteria, including agronomic performance, product quality, and sustainability. Farm-scale experiments can be useful in assessing environmental criteria because they provide the platform for full biogeochemical nutrient cycling studies: within the soil itself, between soil and water, as well as soil and the atmosphere. 

In addition, the role of plants and livestock in these nutrient cycles can also be studied. Such studies also enable investigation of the effects of climate and management on water, nutrients, and carbon cycling. The regulatory environment has tightened, concerns about personal and environmental safety are on the rise, and the cost of research and development has increased substantially.

So how can Agriculture big data analytics help with field scale trials?

Running Flawless Trials

The essence of successful agriculture trial data reporting lies in impeccable trial operations. Achieving this involves complex logistics, meticulous management, and end-to-end oversight – from the blueprint of layouts to the judicious allocation of resources and budgeting. Any mistake not only inflates costs but can also jeopardize the trust built with clients. 

Enter Agriculture data analytics:

  • Real-time Visibility: With the aid of an agronomic field research dashboard, CROs can monitor trials in real time, ensuring timely interventions and corrections.
  • Informed Planning: Legacy data serves as a treasure trove, offering insights to sidestep past errors and streamline the planning process.

Adhering to Sponsor Protocol

Meeting and exceeding sponsor expectations remains the bedrock of any service industry. In agricultural trials, clients often stipulate protocols which, while ensuring precision, might demand considerable time and resources.

However, agriculture data analytics changes the game by providing:

  • More diverse Data Collection: Utilizing sensors, drones, and collected data, it continuously monitors trials, ensuring rigorous adherence to protocols.
  • Enriched Planning: Legacy data aids CROs in their dialogues with clients, furnishing insights that ensure the trial’s blueprint aligns with success.

Service providers, such as agricultural input suppliers, cooperatives, agricultural extension organizations, and NGOs, need to make recommendations to farmers, considering many different criteria (and trade-offs between these criteria) in different environments and under diverse types of crop management.

Managing Workflow and Field Assignments

Orchestrating a field trial team, especially against the backdrop of unpredictable weather and varying field conditions, is challenging. Analytics and reporting in agriculture field research help navigate this challenge by:

  • Efficient Tasking: Streamlining task assignments and creating schedules that factor in workload, weather predictions, and on-ground conditions.
  • Resource Optimization: Analytics ensure resources are deployed where they are most needed, ensuring cost-efficiency.
  • Monitoring and Communication: Progress and performance metrics are tracked in real time, fostering enhanced collaboration and minimizing communication overheads.
  • Documentation Automation: By automating reporting, ag data analytics ensures every decision and change is well documented, minimizing errors.

Streamlining Data Management and Integration

Despite improved technology, in many agronomic field trials data is still entered manually. The data essential for trials isn’t confined to field readings; it spans weather data, readings from soil probes, drone-captured data, and more.  

Agricultural data analytics bridges these diverse data streams by providing:

  • Harmonized Data: Data from disparate sources is automatically aligned and harmonized, to ensure consistency. Crop variety trial datasets are often very heterogeneous in terms of quantity, quality, types, and formats. Problems with different data sources include a lack of standardization in terms of syntax, semantics, and structure. 
  • The ability to review multiple sources: Through data dashboards for agronomic research analysis, clients can seamlessly peruse data from varied sources, enhancing the value proposition of research services and collaboration.

On-farm experimentation (OFE) describes innovative approaches to agricultural research and innovation that are embedded in real-world farm management and reflects new demands for decentralized and inclusive research that bridges sources of knowledge and fosters open innovation. 

Digitalization enables OFE by dramatically increasing scales and complexity when investigating agricultural challenges.

Easy Reporting for Clients and Compliance

Whether a client needs intermittent updates or a comprehensive report at the trial’s conclusion, managing this vast data, especially with compliance mandates in play, is critical. Ag data analytics addresses this by:

  • Real-time Access for Clients: Ensuring clients can access up-to-date data whenever they need, fostering transparency.
  • Automated Reporting: With agricultural field research dashboard tools, reporting is not only automated but can also be customized based on client requirements, trimming unnecessary communication and bolstering collaboration.
  • Compliance: The precision of ag data analytics ensures that reports can be trusted for compliance, reducing risks of non-conformance.

Agmatix: Leading the Charge for CROs

In an era where data drives decisions, Contract Research Organizations (CROs) in agriculture are rapidly recognizing the power of agriculture data analytics to revolutionize their operations and improve product development. Agmatix taps into the immense potential of analytics and reporting in Ag field research data and advanced AI. 

Agmatix isn’t just a solution; it’s a radical shift in agriculture trial data reporting. Its capabilities, from simplified reporting and global trial management from a central platform to managing diverse teams and ensuring end-to-end oversight, position it as an invaluable asset for CROs. 

Agmatix offers effortless collaboration among stakeholders by granting authorized users data access that can be permission-based. This allows researchers, agronomists, team members, and others to easily view, analyze, and report on the collected data, regardless of their geographical location. 

Agmatix empowers stakeholders to make data-informed decisions and draw invaluable insights and the mobile app ensures accurate and streamlined data capture, whether online or offline. 

Generating customized reports is easy, tailoring them to include all necessary details about protocols, and treatments. The solution effortlessly collects and compiles data from various locations, being immediately accessible for all stakeholders to view, analyze, and report.

Agmatix also understands the critical need for regulatory compliance and the importance of data security and privacy. By utilizing our secure cloud-based SaaS platform, data remains protected and accessible only to authorized personnel.

As the AgTech industry evolves, platforms like Agmatix can ensure the journey is not only data-driven but also sustainable and productive. For every stakeholder, from growers to researchers and strategic partners, this convergence of technology and agriculture heralds an abundant future. Our proven Trial Management Saas platform is available now. Learn more at

Sustainable Agriculture Data and Digital Monitoring (D-MRV)

The world is undergoing a paradigm shift with sustainability issues becoming increasingly important, along with greater and greater use of sustainable agriculture data. More than ever, there’s a pressing need for sustainable practices, especially in sectors that significantly impact our environment such as the food supply chain. 

By harnessing the power of technology and big data analytics —a cornerstone of data science for sustainable agriculture —  farmers and growers can optimize their practices and farming systems. This approach enables them to reduce their consumption of finite resources such as inorganic fertilizer, and minimize their environmental footprint. 

Digital monitoring and verification ensure that sustainability efforts are implemented and adhered to, promoting transparency and accountability in the agricultural sector. In addition, monitoring and verification can allow farmers to tap into additional revenue streams through carbon credit markets.

This article looks at why sustainability is so important to agriculture and the food supply chain, and how big data and digital monitoring can help farmers and agronomists achieve sustainability goals. 

Why Sustainability Is Essential: The Underlying Need

Sustainability, increasingly influenced by the use of data science for sustainable agriculture, is the central concern of modern society and is significantly affected by the goal of agriculture in seeking to guarantee food security for the ever-increasing population with limited natural resources. The need for sustainability in agriculture is impacting all parts of the food supply chain. Agriculture is responsible for approximately 18% of global GHG emissions and more than 75% of global N₂O emissions

Synthetic fertilizers, transportation, and field applications are major contributing factors to direct GHG emissions from agricultural activities. More effective farming operations, reduced uncertainties and risk, and improved real-time decision-support could revolutionize agriculture and reduce its environmental impact. 

The Food and Beverage (F&B) industry is a pivotal player in this transition and is evolving rapidly to meet these demands. But what’s powering this transformation? The answer lies in sustainable agriculture data and the increasing role of data science in sustainable agriculture.

Food and Beverage Companies

The Food and Beverage (F&B) sector, amidst the throes of global environmental challenges, finds itself in a unique position. With increasing awareness and the need for accountability, companies are moving towards a more transparent, sustainable approach.

According to Deloitte Scope 3 (indirect) emissions are particularly significant for F&B  companies. They can comprise up to 95% of their total carbon emissions, with the bulk of emissions arising from agricultural production and from land use change within their supply chains. Measuring, monitoring, and managing Scope 3 emissions is critical for F&B companies to comply with their carbon reduction commitments.

F&B companies are moving towards more efficiently tracking their sustainability initiatives. Such actions not only foster trust among stakeholders but also provide these firms with a competitive advantage, as consumers become increasingly aware and influenced by sustainability issues. 


Modern consumers, equipped with information and choices, prioritize sustainability like never before. They crave transparency and traceability, wishing to know where their food comes from and how it’s produced. 

Digital technologies also have the potential to offer consumers greater transparency as to how their food is produced. They offer opportunities to renew business models in value chains by connecting producers and consumers in innovative ways.

By tracking sustainable agriculture data, F&B companies can effectively report on their growers’ field-level efforts to reduce Scope 3 emissions. This allows consumers to gain a clearer understanding of the environmental impact of their food choices, leading to more informed decisions and growing demand for sustainably produced products. Such advancements not only cater to consumer preferences but also contribute to a more environmentally conscious and responsible food industry.

Farmers and Growers

For farmers and growers, the stakes have never been higher. With climate change altering landscapes and weather patterns, there’s an urgent need to optimize resources and employ sustainable farming. With climate change altering landscapes and weather patterns, there’s an urgent need to optimize resources and employ sustainable farming to increase their field’s soil health and resiliency to weather extremes. Agricultural monitoring systems empower growers with more accurate and actionable data, offering insights into sustainable practices, and ensuring long-term viability.

What is MRV in agriculture?

Measurement, Reporting, and Verification (MRV) in agriculture refers to the multi-step process to measure the amount of greenhouse gas (GHG) emissions reduced by a specific mitigation activity.. For example, implementing improved farming practices can lead to a significant reduction in GHG emissions over a defined period. The effectiveness of such practices is then reported and verified, ensuring credibility and transparency. Transparent MRV processes are critical for making tangible progress in reducing GHG emissions. Recognizing its importance, the UN has developed a comprehensive handbook on MRV, specially tailored for developing countries. This handbook serves as a vital resource, guiding these countries in effectively implementing and benefiting from MRV strategies.

The Carbon Credit System: A Double-Edged Sword

The current carbon credit system, designed to incentivize businesses to reduce emissions, has its set of advantages and is growing rapidly. In 2021, the voluntary carbon market reached $2 billion—four times its value in 2020—and the pace of purchases was still accelerating in 2022. By 2030, the market is expected to reach between $10 billion and $40 billion.

However, a focus on carbon emissions is a simplification of the multifaceted issue of sustainability which includes both economic and social concerns as well as other environmental issues such as biodiversity. While it generates additional income for producers, the system often does not address broader environmental concerns, such as biodiversity, and a more holistic approach is often required. 

In addition, estimating and verifying carbon sequestration requires monitoring and collecting large amounts of farm-level data, which industry leaders can use to build market power potentially to the detriment of the market position of farmers. 

Carbon credit systems are not perfect and more robust and equitable systems are needed, but they are a tool to help the transition to more sustainable food systems.

The Path Ahead: Embracing a Comprehensive Sustainability Approach

Moving beyond the narrow lens of carbon emissions, there’s a growing realization of the importance of a holistic approach. By integrating big data, F&B companies can delve deeper into multiple sustainability metrics such as water usage, waste management, and biodiversity. 

This shift towards a broader perspective, powered by D-MRV, addresses the limitations of the carbon credit system, presenting a more rounded view of sustainability. In this context, big data becomes a cornerstone, reshaping the carbon credit landscape and sustainability reporting.

Digital technologies can help reduce the environmental impact of food production as well as improve production quantity and quality while reducing labor requirements. However, these technologies can only succeed if agronomic data companies have access to the data required to identify trends, correlations, and causation. 

Having access isn’t enough – agronomic data companies must be able to ingest and use the data to provide actionable insights which require it to be in a singular, standard format

Agmatix’s Role in the Sustainable Agriculture Data Revolution

Agmatix, with its unwavering commitment to sustainability, is redefining the norms and can help Ag Input suppliers build stronger relationships with their growers. 

The company’s Digital Crop Advisor stands out, leveraging data to monitor crucial sustainability KPIs (Key Performance Indicators). This digital agronomist tool enables them to work directly with growers in the field. 

The digital Crop Advisor solution gives field agronomists instant access to all their product listings so they can create the best crop nutrition management plans for their growers’ fields. This helps to optimize their customer’s yield and quality through scientific-backed recommendations as their trusted partners.

But what truly distinguishes Agmatix is its comprehensive sustainability framework. Agmatix’s approach provides more than simple carbon metrics, offering a 360-degree view of sustainability. 

Agmatix’s crop nutrition optimization solution provides sustainable nutrient recommendations based on a unique carbon footprint analysis. This allows you to quantify and compare sustainability KPIs (carbon footprint, nitrogen leaching) for customers with other plans developed in the past, or other fields using our technology.

Harnessing the Power of Sustainable Agriculture Data: From Efforts to Outcomes

One of the groundbreaking advantages of using sustainable agriculture data is the capability to link farmers’ endeavors to tangible outcomes. This connection opens doors to ‘what-if’ scenarios, a strategic tool that can be a momentous change. 

For instance, through Agritech analytics, F&B companies can simulate the impact of changing irrigation methods or adopting a new crop variety, providing actionable insights for both growers and companies.

Validation Efforts: Insights from India and Brazil

In a bid to enhance its sustainability initiatives, Agmatix has undertaken validation studies in the diverse agricultural terrains of India and Brazil. These efforts have yielded crucial findings, enriching the company’s repository of sustainable practices and insights. 

Agmatix has partnered with NASA Harvest – NASA’s global Food Security and Agriculture Consortium – to support crop production sustainably at the field level and mitigate the impact of climate change. The collaboration will promote resilient agriculture beginning with smallholder farms in different parts of the World. 

A combination of ground sampling and remote sensing data will be used to support these farmers in their transition toward sustainable agriculture. The methodology developed within this partnership will track farmer efforts to improve conservation management and guide them to improve their sustainability levels.

In India, Agmatix has also started working in collaboration with local agronomists on data from 45 commercial vineyards. This is helping agronomists recommend, and optimize nutritional requirements for crops and reduce fertilizer use, as well as improving economic performance. Additionally, expansions in the Brazilian soybean market are underway, marking a significant step for Agmatix in extending its sustainable agriculture efforts into another key global agricultural sector.

Concluding Thoughts

In the face of mounting environmental challenges, the power of big data and tools like D-MRV can’t be overstated. The F&B sector, bridging the gap between consumers, growers, and producers, finds itself at the center of this change. 

By integrating sustainable agriculture data, not only can we ensure a brighter future for the planet but also create a sustainable, transparent, and resilient agricultural ecosystem for generations to come.

Agmatix empowers agronomists and agriculture professionals with the most accurate, science-based crop benefits and agronomic decisions to not only drive sales and optimize crop yield and nutrition but also enhance sustainability. To find out more about how Agmatix can enhance the sustainability of your business through the plant nutrition carbon footprint optimizer click here.

Advancing Sustainable Growth: The Role of Agriculture Data Analytics in Regenerative Agriculture

Introduction: What is Regenerative Agriculture?

Regenerative agriculture is emerging as a pivotal approach to farming, gaining prominence for its potential to address sustainability challenges in the face of climate change and a burgeoning global population. In this blog, we will look at the significance of regenerative agriculture and explore how data analytics tools can propel it into a new era of efficiency and sustainability.

So, what does regenerative agriculture mean? Regenerative agriculture involves farming practices that restore and enhance soil health, biodiversity, and ecosystem services. The term itself was first used by the Rodale Institute in the 1980s. According to one of its proponents, Gabe Brown regenerative agriculture not only fixes farming, but also the farming business model. 

Regenerative agriculture is seen as an essential means of reducing or mitigating GHG emissions. Other benefits of regenerative agriculture are said to include more nutritious food, healthier rural culture, and enabling smallholder growers worldwide to feed themselves and the rest of us. 

Principles and Practices of Regenerative Farming

Agriculture, perhaps more than any other industry, finds itself on both sides of the climate change equation – being both a source of GHG emissions, as well as a potential means to sequester carbon. 

Regenerative farming doesn’t have a singular definition, as outlined in the comprehensive review by Schreefel and colleagues in the 2020 publication of the Global Food Security journal. A recent study on UK farmers revealed encouraging trends: over 60% demonstrated a keen awareness, with more than 30% actively adopting highly sustainable soil management practices, particularly among mixed and arable farmers. Notably, an overwhelming 92% of respondents identified themselves as practitioners of sustainable soil management.

Regenerative agriculture, while lacking a universally accepted definition encompasses several regenerative farming practices worth noting: 

  • Avoiding or limiting plowing or soil disturbance, to maintain the soil structure and fertility;
  • Covering the soil surface with a plant or organic cover through cover crops to prevent soil erosion and water loss;
  • Keeping live roots in the soil, to feed the beneficial microorganisms that contribute to plant and soil health;
  • Using crop rotations. This means growing a variety of crops, to increase biodiversity and resilience to biotic and abiotic stresses;
  • The integration of livestock in arable rotations. This includes ruminants as well as allowing chickens, pigs, geese, and ducks to pasture freely. Manure will supplement the nutrient cycle and improve forage quality.

The Role of Data Analytics in Modern Farming

Analysis shows that growers combine practices in diverse ways and that growers do not always follow the full set of regenerative agriculture principles of reduced soil disturbance, soil cover, and crop diversity.

As we face the dual challenges of feeding a growing population and mitigating the impacts of climate change, regenerative agriculture stands out as a beacon of hope. The emphasis on improving soil health, reducing environmental impact, and fostering resilient ecosystems aligns seamlessly with the urgent need for sustainable agricultural practices.

Agriculture Data Analytics: A Critical Path to Regenerative Agriculture

The emergence of agricultural data analytics marks a significant difference in the way we approach farming. It marks a shift towards more sustainable and regenerative farming systems by dramatically improving decision-making in real-time. This leads to increased productivity, reduced costs, and diminished environmental impact. 

Regenerative agriculture is not one size fits all. The best combination of practices might vary depending on the production environments, as crops, soil, and climate vary across space. Identifying the best practice for a specific location is challenging and often involves an iterative experimental process of trial and error. Over time, adopting regenerative practice improves soil health, and in some cases, also contributes to higher yields (i.e. van-Es and Karlen, 2019 SSSA journal).  

The efficiency of this process can be accelerated and become more efficient when digital tools are used to plan, collect, and analyze the results. These tools enable efficient trial management and transparency in project and experiment stages. On top of the clear benefits of data preservation, once big data is accumulated, trends and models can be generated to explore and identify what practice works where.

Carbon capture is a crucial aspect of regenerative farming, and the emergence of carbon markets and offsetting may provide an additional income stream for some regenerative growers. However accurate and independent data on soil carbon and farm practices are needed to make these markets operational. 

Remote sensing can play a crucial role by monitoring practices such as tillage, at scale. The ability to do efficient crop scouting at scale can help growers apply an adaptive approach to crop protection, and reduce routine crop protection applications. Remote sensing can aid in identifying irrigation problems and inefficiencies, reducing the field water footprint. Beyond merely monitoring crop growth, it plays a crucial role in crop protection, detecting early signs of disease, pest infestations, or nutrient deficiencies. 

This technology not only enables targeted interventions, ensuring timely and effective treatment but also minimizes the carbon footprint and environmental impact associated with these practices. Additionally, remote sensing offers a scientifically based measuring system that helps verify the environmental credentials of crops grown for supply chain.

Finally, collecting data in a digital, standardized way enables data sharing between different stakeholders, learning from the experience of peers, or allowing comparison between different geographies and crops.

A USDA blog post emphasizes the role of big data in improving farm incomes and helping the environment. Data analytics not only facilitates a better understanding and application of agricultural practices but also identifies areas for improvement. This is essential for achieving sustainability goals in agriculture. 

Data Helps to Understand Agriculture’s Environmental Impact

The limitations of traditional data collection methods become clear when seeking a global and scalable view of agriculture’s impact on the environment. Data will be central to scaling up regenerative agriculture. Regenerative agriculture is not a return to traditional farming practices but is reliant on technology including data science. 

Data helps growers and other stakeholders better understand agriculture’s impact on the environment and is critical to enabling progress and adopting new regenerative practices on farms. We can only capture the necessary data globally and at scale through advanced data analytics, generating accessible datasets crucial for informed decision-making.

The Agmatix platform, with features like Agronomic Trial Management and Digital Crop Advisor, can play a pivotal role in overcoming these challenges. By facilitating granular data capture and defining key indicators of regenerative agriculture on a large scale, these tools empower growers and agronomists to make more informed decisions.

Agriculture Data Analytics Enables Regenerative Ag Decision-making

Granular data capture and agriculture data analytics are just the beginning; machine learning and artificial intelligence (AI) can take regenerative agriculture a step further by enabling predictive modeling and broader insights. These technologies provide actionable information that supports decision-making at various stages of the farming process.

Predictive analytics allows us to look at ‘what if’ scenarios. For example, they could allow us to understand and identify supply chain constraints before they become a market issue. By analyzing the impacts of sourcing different crop products buyers can identify the most sustainable crop products within their specific supply chain. Predictive analytics can also optimize resource usage or crop management. By analyzing historical data, weather patterns, and soil conditions, these tools can recommend precise interventions, reducing waste and maximizing yields. These advances are instrumental in the pursuit of regenerative agriculture goals.

Agmatix and AgTech for Regenerative Agriculture

Agmatix emerges as a key player in the realm of agtech for regenerative agriculture, offering solutions that enable a deep understanding of product sustainability. The platform’s features, such as Digital Crop Advisor, empower agronomists to collaborate with growers to optimize crop nutrition plans. This collaborative approach is crucial in addressing the complex challenges of regenerative agriculture and fostering partnerships between the public and private sectors. 

The Agmatix Digital Crop Advisor, in particular, opens up avenues to explore a variety of different products from different sources. This flexibility allows for a tailored approach to regenerative agriculture, in keeping with the lack of consensus on a definition and acknowledging the diversity of landscapes, crops, and farming practices.

Fostering Collaboration for Sustainable Agriculture

The journey towards regenerative agriculture requires collaboration on a global scale. Agmatix, by fostering collaboration across the food supply value chain, contributes to the creation of a sustainable and regenerative agricultural ecosystem. The Agmatix platform allows for the easy and secure sharing of data between partners. The exchange of knowledge, data, and best practices becomes essential in overcoming the challenges faced by the agricultural sector.


Data analytics technology in agriculture is a linchpin in the journey towards regenerative agriculture. By overcoming the limitations of traditional data collection methods, advanced technologies pave the way for a more sustainable and efficient farming future. 

Agmatix’s data analytics tools, including Agronomic Trial Management and Digital Crop Advisor, play a crucial role in this transformation, offering growers and agronomists the insights needed to make informed decisions and contribute to the global effort for a more sustainable and regenerative agricultural sector.

As we navigate the complexities of agriculture’s transition to sustainability, the integration of data analytics technology becomes not just a choice but a necessity for a thriving and resilient future.

Jumpstart Your Field Trial Season with Cutting-Edge Software

The methods and tools for agricultural research data analysis are advancing rapidly. The increased adoption of AgTech is considered an essential step to address global food security whilst meeting sustainability goals. Agriculture contributes to numerous sustainable development goals however accepted methods for linking research outcomes to sustainability impacts are missing. 

Yet the promise of new technologies does not always carry over from trials to real-life conditions, and the diffusion of many technologies, varieties, and chemistries remains limited. Improved data analytics is needed to make accurate predictions at the farm level that can lead to more cost-effective, sustainable, and environmentally sound agricultural production. However, the quality of the information obtained from a trial is only as good as the rigor applied and the interpretation of the results. 

So, what are the challenges in agricultural field trials data analysis, and how can cloud-based tools help in planning field trials, collecting, disseminating, and analyzing data? Challenges include the cost of running agronomic trials which add considerably to the costs of bringing new products to market. A well-planned trial increases the likelihood of success and is easier to implement, manage, and report. However, trials require a lot of dedication and the investment of time and money. 

Along with financial aspects, agricultural field trials face additional critical challenges, including the complexities of data movement and sharing, communication hurdles, legacy system limitations, and issues in both short-term and long-term data collection and analysis, all of which profoundly affect efficiency, data integrity, and the effective adoption of new technologies. Let’s dive deeper into these challenges and explore their implications.

Legacy Solutions Bring Complexity to Agricultural Research Data Analysis

The intricate layers of planning, data collection, analysis, and presenting the results bring in complexities, especially for Ag Input companies and Contract Research Organizations (CROs). This complexity is accentuated when the weight of legacy solutions and practices is added to the mix.

The digital revolution has transformed most industries and can transform agricultural research data analysis. Yet the adoption of new technology within the agricultural sector often lags other industries and some practices in agronomic research still rely heavily on legacy solutions. These methods, while tried and tested, often act as bottlenecks in the swift progression of trial management. 

Long production cycles within farming and the need to consider the long-term environmental and sustainability impacts of farming methods and systems means that agricultural research is a long-term activity. Many field trials often last years. There is a need for a long-term understanding of farm production systems, technologies, and varieties, and a need to integrate and analyze older data. 

Data Movement and Sharing

Transferring information between systems and stakeholders using older methods is tedious and can lead to potential data loss or misinterpretation. Traditional methods of moving and sharing data, like on-prem systems, are not just time-consuming but fraught with risks. Lost or corrupted data can set back trials by months.

New methods such as data-driven decentralized breeding (3D breeding) can scale up varietal testing in larger sets of environments. This approach leverages extensive datasets and collaborative networks of breeders to enhance the precision and efficiency of crop improvement by analyzing genetic, environmental, and historic performance data. Furthermore, by targeting farmers’ evaluations, 3D breeding can significantly speed up genetic improvement. This can contribute to closing the gap between expected and realized gains in improved crop technologies. 

Communication and Collaboration

Legacy means of communication, whether it be through fragmented email chains or paper correspondences, are slow and prone to miscommunication. Legacy methods do not have the immediacy and efficiency of modern communication tools. This hampers swift decision-making and on-the-fly adjustments. 

New cloud-based agronomic field trial data collaboration tools offer a seamless way to share information with colleagues in different locations, and institutions in real-time. 

Data-driven approaches build on larger volumes of data and flexible analyses that link different datasets across domains and disciplines. The use of large datasets and computational methods has transformed the practice of crop breeding. 

Data Collection

The age-old practice of using pen and paper is not only time-consuming but is also prone to human error. New agronomic data collection tools offer real advantages. Think about the contrast between jotting down observations with a pen on paper versus instantly inputting and syncing data via a mobile app. 

The former can be inaccurate, inefficient, and doesn’t allow real-time collaboration. Compare this with a mobile app where data is uploaded in real-time with minimal inaccuracies.


Post-trial data wrangling on Excel sheets feels archaic and can be prone to human error. Agricultural field trial data analysis is a time-intensive process that often muddies the clarity required to draw precise conclusions. 

A data-driven approach can analyze complex interactions, allowing crop breeders to deal with trade-offs in improving a larger set of complex traits while maintaining diverse breeding populations. This potentially helps combine production traits with quality, use, and environmental traits, guiding genomic selection toward the establishment of multiple allele pools targeting local needs.

Cloud-Based Solutions Move the Starting Line Forward

Agronomic trials are generating more and more data. For example, novel sensor technologies have drastically increased the amount and diversity of phenotypic data from agronomic field trials. Data from agronomy experiments are typically collected and stored in multiple minimally documented computer files. 

Additional information is also often entered and archived in field books or diaries. This means that data manipulation is generally cumbersome and error-prone, and data loss is frequent.

However, cloud-based solutions are changing the game for agronomic research. Planning crop trials and the analysis is easy when all data is in a single place. Instead of disparate pieces of information scattered across different platforms or tools, all data is aggregated and stored in a single, accessible place. Holistic cloud-based systems make this seamless integration possible, reducing the friction often associated with trial planning and execution.

Unified Data Storage: Having all your data in one accessible place means no more searching through piles of paperwork or different systems. Everything is instantly accessible, making the decision-making process more agile.

Holistic Approach: Agronomic cloud-based solutions and tools provide an all-encompassing platform where data collection, analysis, and communication can happen seamlessly. This integration reduces friction, ensuring trials progress smoothly.

Agmatix: The Dawn of a New Agronomic Tomorrow

The Agronomic Trial Management solution by Agmatix is not just another tool; it’s a paradigm shift within agriculture data analysis. Its capabilities allow data to cascade smoothly across systems and locations, offering:

  1. Advanced Data Collection Benefits: Emphasizing real-time data collection tools ensures timely and accurate information, minimizing lags and errors. With tools tailored for next-gen field trials
    Agmatix ensures that data is collected accurately, efficiently, and in real-time. Agmatix’s Agronomic Trial Management solution ensures data moves without hitches, from collection to analysis, ensuring decisions are based on the most current data.
  2. Legacy Trial Data Integration: Agricultural research software from Agmatix allows teams to integrate older trial data, ensuring continuity and a comprehensive understanding. Recognizing the value of historical trial data, Agmatix facilitates the smooth integration of this data, ensuring a richer database for analysis.
  3. Strengthened Collaboration: Whether it’s between departments, with CROs, or between CROs and their clients, seamless collaboration is facilitated by the efficient sharing of data. Whether it’s inter-departmental collaboration or communication between CROs and their clients, Agmatix provides tools that foster seamless teamwork.
  4. Operational Efficiency: A 360-degree view of trials, tasks, workloads, budgets, and real-time data visualization streamlines processes and ensures everyone’s on the same page. From overseeing trials, managing tasks, and monitoring workloads and budgets, to real-time visualization of data, Agmatix brings operational efficiency to the forefront.
  5. Enhanced Data Analysis and Presentation: Armed with tools designed for agri big data analysis, Agmatix simplifies the complex task of drawing insights from vast data sets. This ease of analysis ensures that the results are not only accurate but also presented in a manner that’s easy to understand and act upon. 
    With sophisticated algorithms, data interpretation becomes sharper, enabling better and more timely decision-making. Plus, presenting this data in intuitive, visually appealing formats makes stakeholder communication more impactful.
  6. Insightful Connections: Agmatix stands out in allowing single and cross-trial analysis. The capability to connect insights for both single and cross-trial analysis ensures a broader perspective, which is invaluable in agronomic research. This interconnected approach paves the way for insights that can be pivotal for success.

Agmatix turbocharges the trial process and agricultural research data analysis. The platform not only facilitates faster data collection and analysis but also ensures a quicker time to market for new varieties and products. As the adage goes, time is money. In the world of agronomic research, Agmatix proves that this has never been truer.

To delve deeper into the transformative power of next-gen field trials, explore here. For insights into how agriculture data analysis is shaping the future, click here. Finally, to understand the synergy between precision agriculture and big data analysis, journey through our in-depth exploration here.

Streamline Field Trials with Next-Generation Digital Solutions 

Managing field trials requires a complexity of tasks. It is more than simply performing an experiment and collecting data. Agronomic researchers are tasked with managing trials, field technicians, and collaborating with other research organizations and managers. Beyond that, they must monitor data collection to meet protocol standards, navigate large data sets, and be able to communicate trial outcomes.

Managing field trials means juggling a lot of moving pieces, sometimes all at once. Currently, many ag input companies and CROs are using multiple platforms to manage different responsibilities.

Agmatix is an end-to-end, cloud-based SaaS solution that helps bring these variables together and streamline the trial process. This solution will help research teams communicate more effectively, manage tasks, easily share information, and analyze trial data, all under one united platform.

Manage Multiple People on a Single Platform

Imagine a tool that will enhance the collaboration of your agronomic research team.

Timing is everything when collaborating with others in agronomic research. Whether it’s working with a team of field technicians to ensure the timely planting or application of a product, or being responsive to other research collaborators, managing communication is an integral part of agricultural research.

When managing multiple field trials, it’s common for many time-sensitive tasks to need management in a short window of time. If these tasks aren’t completed on time, it could jeopardize the integrity of the data or lead to complete trial failure. If this happens, it could further delay the launch of a product that could offer a solution to growers around the world.

Enhancing Precision: Real-Time Task Monitoring

With the end-to-end, cloud-based Agronomic Trial Management tool, research teams can track tasks in real time. This is an agronomic research collaboration tool that unifies research teams and reduces trial error due to faulty timing. It also assists in standardizing the research process to enhance data quality.

Cross-Organizational Collaboration

Beyond collaborating with internal research teams, researchers must also collaborate with experts from various organizations such as universities, extension offices, and government agencies. Sometimes this communication must cross both time zones and language barriers. With the need to meet constant deadlines, the need to find an efficient and effective way to communicate is ever-growing.

Timely Responses in a Digital Age

In the technological world that we are in, there is a growing expectation for timely responses. These expectations aren’t unwarranted. We live in an exciting time where experts from various organizational backgrounds, from around the world can collaborate with one another and make a difference every single day. This wouldn’t be possible without the technology we have to support quick and timely communication.  

Field Dynamics and Quick Solutions

The environment in the field can change quickly. Whether it is trying to diagnose an issue or report on research findings, quick communication allows experts to understand agronomic issues and bring solutions to market faster. This is why an agronomic research collaboration tool will aid in revolutionizing the future of agriculture by uniting research teams and enhancing information sharing.

Agronomic Trial Management Makes People and Task Management Easy

Share protected information efficiently with cloud-based technology. This technology offers an authorization protocol that allows users to give access to information to authorized users. This protects information from being accessed by unauthorized individuals. When managing multiple teams with individuals of varying degrees of informatio nal access, this tool allows for easy collaboration with high-quality protection.

With the Agmatix field trial technology, ag input companies and CROs can streamline operations while standardizing methods to enhance quality of the data, all on one integrated dashboard. They can rest assured that their information is protected, while easily accessed by those who need it.

Easing the Stress of Managing and Locating Multiple Datasets

A single trial often contains multiple datasets. In seed trials, many different data points may be recorded, such as how varying environmental factors play a role in crop development.  For crop protection and nutritional products, research teams may need to look at product efficacy at different timings, rates, and with different tank-mix partners to ensure crop safety and product quality. Most trials are also performed across multiple locations and seasons.

The Value of Historical Data in Research

Historical trial data can be just as important as emerging research. This data may be important to meet regulatory requirements and can act as a foundation for new research. It is also important when performing a cross-trial analysis.

Legacy Files: Challenges and Modern Solutions

Some data, such as legacy files, may be housed with outdated storage methods. These may include past trials that were performed, with data saved on early versions of Microsoft software or on outdated storage technologies such as floppy discs, zip discs, or older hard drives. With these older forms of data storage, there is an incompatibility risk when transferring that data to more contemporary formats. This incompatibility could lead to data loss or inaccessibility of information.

Standardization and Organization Issues

Beyond the potential loss of data, these legacy files may lack standardization when it comes to file organization and storage. Saving a file under a different folder or using a different name may make it difficult to find it years later. 

Embracing Next-Gen Digital Solutions

Though traditional storage methods for legacy files may still serve a purpose, converting and storing those files onto a next-gen digital platform can assist in preserving information and historical data.

This not only aids in access to historical data but can also help researchers access data that has been collected and saved in different units or languages. Using modern technology, organizations can efficiently reduce information loss due to language barriers and perform cross-trial analyses with ease.

This leads to faster access to information when it is needed. This capability may streamline the process for cross-analysis or expedite the process of providing information to regulatory groups.  

Agmatix Cloud-Based Solution & Easy Data Management

Safely store data in real-time with the agronomic trial management tool by Agmatix. Collect data in the field using digital software that works both on and offline. This data will be stored and easily accessed by all authorized users. These files are safely backed up using cloud-based SaaS technology. This technology helps prevent data loss issues due to mislabeled documents, language barriers, and outdated storage formats.  

With this agronomic analysis software, researchers can view all their agronomic data in a unified place. This tool assists with agronomic database analysis with pre-built statistical tools and widgets that users can utilize to build custom reports quickly.

One Dashboard to Manage Multiple Priorities

Many responsibilities come with managing trials. Some of these responsibilities include data security, managing trial data integrity, and meeting deadlines. These responsibilities can have an impact on both speed to market as well as customer service.  

 Managing data security can be a stressful, yet important responsibility when working with sensitive information. Having a safe way to secure and share data is a growing need. Cloud-based SaaS technology stands out as an optimal solution to secure this information on a united platform that is accessible on multiple devices to authorized users.

Seamless Data Collection and Accessibility

Beyond securing data, researchers are also tasked with managing trial data integrity. This requires the adoption of standardized processes and utilizing modern technology that allows data to be collected and stored in a single platform. The ability to access data in real time can significantly expedite the process of data analysis and report generation. Photos, videos, and notes can easily be attached to trial documentation with the click of a button while standing in the field.This technology helps streamline various aspects of the research process, making researchers better equipped to meet deadlines and stakeholder expectations.

Data Collection via Mobile with Offline Capabilities

Agmatix’s Agronomic Trial Management tool simplifies the process of data collection. It allows you to collect data in the field from your mobile devices, even in remote locations, thanks to its offline capabilities. Furthermore, it streamlines data collection and data entry into a single step, reducing the risk of human error and information loss.

Agmatix Makes Managing Priorities Easy

Agronomic research comes with its fair share of challenges, but Agmatix is here to streamline agronomic research collaboration and simplify the process. Our Agronomic Trial Management tool doesn’t just manage your priorities — it supercharges them, boosting operational efficiency by up to 20%. The result? Products hitting the market faster, bringing solutions to growers and researchers in record time.

One of the primary challenges in the field is agronomic compliance reporting. This vital step ensures adherence to regulatory standards. While historically time-consuming, our tool helps to condense what was once a days-long process into a few hours, making database analysis more efficient.

But it’s not just about speed. It’s about offering a holistic solution to agronomic researchers. With Agmatix, you can seamlessly integrate processes, foster better communication, bolster data security, and create a standardized approach to your work. It’s a comprehensive suite designed to elevate every aspect of agronomic research, from collaboration to cross-trial analysis.

In an ever-competitive and rapidly evolving landscape, tools like the Agmatix Trial Management platform aren’t just nice-to-haves — they’re essential. Stay ahead, meet your milestones, and exceed stakeholder expectations, all while safeguarding your data. Experience new-generation agronomic research with Agmatix.

Next-Gen Agronomic Trial Management

The Agmatix Agronomic Trial Management System is transforming how professional agronomists and researchers plan and manage vital field trials. A suite of sophisticated field trial data tools significantly reduces the cost and duration of trials, shortening the time to market for new agronomic products. A smooth transition to the end-to-end system of field trial data software is a readily obtainable solution for trial managers. 

Identifying Obsolete Field Trial Data Management Practices

The essence of agronomical research is innovation and the ability to successfully identify practical applications for new technologies and concepts. Unfortunately, human beings are usually creatures of habit. Even in a work culture that demands constant experimentation and a search for solutions, there is a tendency to unquestioningly rely on the established ways of doing things. 

The world’s most talented scientists and researchers are usually highly goal-focused and can become immersed in advancing their particular fields of expertise. Trial managers in particular can easily be oblivious to their dependence on outdated processes and procedures when they are conducting research and trials. It’s not unusual for trial managers to use the same methods and tools for managing agricultural field trials that previous generations depended on. 

It can sometimes be difficult to determine whether trusted and familiar methods, that have been proven over time, are an asset or a liability. Agronomic trials can be highly expensive and also require a major investment of time and energy from many different stakeholders and clients. Even when there is a sense that trials aren’t reaching their full potential, there is a natural reluctance to question existing practices and structures that everybody is familiar with. 

The scientific community and professional agronomists are attempting to meet the challenges of feeding a global population that is expected to reach 9.8 billion by 2050. They are simultaneously working to allow agriculture and food production to adapt to climate change and extreme weather events. The underlying objective is to achieve the UN’s Strategic Development Goal of Zero Hunger and efficiently conducted field trials are vitally important. We can’t tolerate a situation where trials are compromised, or their potential is restricted by obsolete trial management methods. 

Are Your Tools for Managing Agricultural Field Trials Obsolete?

During the last few years, we’ve seen game-changing technological advances. These include the development of the Internet of Things, advances in AI and machine learning, SaaS cloud storage, mobile technologies, and a host of other innovations. Individually, these new technologies are useful to professional agronomists and can be applied to field trial data management. When advanced technologies are combined to develop field trial data software, the potential to transform how trials are planned and implemented is astonishing. 

It’s definitely worth taking the time to assess the effectiveness of your current field trial data tools and data management software. The chances are that if you’re dependent on traditional practices and procedures, your field trials are operating at only a fraction of their full potential.

An upgrade to the latest field trial data software can kick start the Three C’s of field trials: collection, collaboration and compliance. If you’re concerned that your trials are inefficient on any level, the following checklist is an excellent starting point for a fuller evaluation. 

Self-Assessment Checklist for Trial Managers and Stakeholders

  • Is comprehensive planning for field trials unnecessarily time-consuming or demanding – do you lack the tools to centralize planning and maintain a broad overview?
  • Are you struggling to manage multiple tasks across your team, especially when stakeholders are located in different geographical locations? Have you outgrown your current solution in scale? 
  • Have there been times in the last year that you’ve been concerned about compliance, or do you waste time implementing compliance measures retroactively?
  • Have there been times in the last year that reporting to stakeholders has become a lengthy exercise in moving data? Do stakeholders receive relevant data in a timely manner and can they utilize data to contribute their full professional expertise to the project?
  • Is your collected data standardized, or is it stored on several different types of files and in different formats – or even across multiple locations?
  • Have you ever lost data or reached the end of a trial only to find out your data quality is poor because of outliers? Are you concerned about data security and how to effectively allocate permissions and access?
  • How much time is your team spending on manual data entry and manual data harmonization? How does this affect team morale, and do data entry requirements function at the expense of other tasks?
  • How many tools, in total, are you using to manage a trial from start to finish? Do you have a single dashboard or interface to connect all stakeholders and collaborators?

If any of these questions highlight issues that you’re currently experiencing, the chances are that you’re working with obsolete field trial data tools and are dependent on inefficient practices. With the new availability of data management software that combines major technological innovations in a single package, weaknesses in trial planning and management translate into serious competitive disadvantages. 

Companies that can conduct a greater number of fast, efficient, and cost-effective trials will significantly outperform competitors who rely on old-school methods. As the new agricultural revolution develops, the stakes have never been higher for companies that seek an increased market share of the agricultural and food production sectors – regardless of their core business or product niche. 

Transitioning Field Trial Tools is Simple and Convenient

The transition to a comprehensive field trial data management solution is a relatively simple process. The initial investment of time and energy isn’t onerous, mainly because the processes involved are logical and the software is user-friendly and actually intuitive. 

When you make the decision to modernize your data management software and embrace a high-tech approach to designing and managing trials, there’s a basic onboarding requirement and the need to learn a new tool. Mastering the tools themselves is essentially a straightforward process. Perhaps the real goal for trial managers is to grasp the full potential of the tools and understand from the offset the extent to which their projects can be transformed, and the freedom that the tools will give them.

One initial requirement is data movement and standardization. Dispersed data and existing databases will need to be standardized into a single format and moved to a SaaS cloud storage facility. Unique machine language and machine learning vastly simplify the process of secure data movement and dramatically shorten the old manual processes. Future data collection and upload is also radically simplified, in turn, streamlining the data analysis process. 

Choosing the Right Field Trial Tool for Your Projects

Every field trial brings its own challenges and parameters. Many are conducted in remote locations or on marginal lands and in sub-optimal conditions for effective testing and data collection. In the past, the tools for managing agricultural field trials had to be selected and tailored for specific projects and were sometimes improvised, or involved detrimental compromises. 

The Agmatix Agronomic Trial Management Solution is a comprehensive end-to-end product that can be applied to every field testing scenario. It rationalizes initial trial planning and makes data collection easy via a mobile app (even when field-level users are working offline). 

As data is collected, the Agmatix Trial Management Solution uses SaaS cloud storage to facilitate seamless collaboration between disparate teams. The Agmatix technology is designed to readily integrate with the user’s system, allowing a convenient plug-and-play solution.  Allocated permissions give users real-time access to standardized data, allowing them to work in sync. As work progresses, project managers maintain a clear overview and clients have full transparency. 

The Agmatix Trial Management Solution not only enhances collaboration and rationalizes separate but simultaneous work processes, it also meets compliance requirements throughout a trial and delivers faster speed to market. Companies that use Agmatix software can achieve a higher ROI on their research budgets and can potentially expand the overall volume and scope of their field testing. 

Agmatix successfully integrates the latest technologies to create a game-changing solution for professional agronomists. As these technologies evolve and improve, the platform is updated to take advantage of the latest advances. Recent updates include comprehensive study design, enhanced collaboration, and streamlined crop protection research. 

Agmatix also welcomes feedback from the world’s leading research institutes, scientists, agronomists, and clients. Their valuable user experiences and insights are analyzed and incorporated into platform upgrades. If you’re conducting field trials, and want to shorten time to market and achieve your full potential, the Agmatix Trial Management Solution has the power to completely transform your operations.

5 AgTech Trends to Watch in 2024

2023 was a challenging and rewarding year in agriculture. The global industry continued to focus on adapting to extreme weather events while overcoming supply chain issues with inputs like fertilizers. As part of the wider impetus to feed the world’s growing population, agronomic researchers and engineering teams worked to develop smart Agtech tools and technologies that address the efficiency and productivity of production agriculture. 

The latest agronomic products and technologies are fueling the urgent transition towards economically viable sustainable agriculture. Major trends in agriculture in 2024 are expected to build on many of the important themes in 2023, with an increased emphasis on generative artificial intelligence (Gen AI), digital twins, and regenerative agriculture.

The Internet of Things, open databases, and cloud technology are helping turn big data into a useful – and accessible – tool – for creating groundbreaking agronomic solutions. These include digital crop monitoring tools, agriculture data enrichment, field data software, and other advanced crop modeling solutions. 

These technologies are anticipated AgTech trends in 2024, as agronomists, researchers, and data scientists harness emerging technologies for use across the entire agriculture value chain. AgTech is a rapidly expanding market and agroinformatics trends top the list of important new developments in the high-tech space. The coming year is expected to create exciting opportunities for innovation in the AgTech industry.

#1: Generative Artificial Intelligence in AgTech

Of all the 2024 trends in digital agriculture, the role played by Gen AI, or generative AI, is likely to be one of the most significant. The potential of Gen AI on the global general economy is already being calculated in trillions of dollars. There is a historic opportunity to improve productivity, eliminate waste and inefficiency, and even open new markets. AI may eventually account for 75% of the value of customer operations, marketing and sales, software engineering, and research and development.

Every aspect of the food industry, from the various agricultural sectors to the diverse food production and distribution components to food retail and recycling, Gen AI is expected to bring major productivity enhancements. Across the industry, Gen AI is anticipated to optimize processes, cut costs, and importantly, fuel innovations through creating new simulations and efficient code.

In agriculture, Gen AI can enhance crop management by optimizing production practices through the analysis of big agronomic data. With AI-supported insights, companies and agronomists can support farmers in adopting precise management techniques and understanding patterns that could influence the performance of crop varieties and production practices on their specific farms. Gen AI can be used to track climate trends and even help farmers become more resilient to the changing climate. 

Agmatix is already developing new agronomic products that use Gen AI and will be at the forefront of Agtech trends in 2024. The Agmatix team leads the industry in using artificial intelligence to harness the potential of big data, develop insights and models to fuel decision-making and produce agronomist and industry-friendly tools to enable sustainable agriculture. 

With this track record of innovation, Agmatix is confidently leading the way towards increasing the use of GenAI in agriculture. The Digital Crop Advisor tool is one example of how Gen AI is already helping agronomists distill agronomic data into effective management recommendations for farmers. Backed by big data, Gen AI, and a desire to support farmers in producing more sustainable crops, Digital Crop Advisor is a key tool for enhancing sustainable crop productivity. 

#2: Utilizing Digital Twins to Optimize Field Trials

A digital twin is a digital model or a virtual representation of an actual physical product (or a system or process). A perfectly accurate digital twin allows researchers and designers to experiment with the model as though they were handling its physical counterpart. Users can leverage real-time or historical data inputs – or a combination of the two (e.g. the Internet of Things and sensor data). 

A significant advantage of digital twins is that they can often be created before the physical product. This transforms the possibilities of typically expensive and time consuming field trials. One AgTech application for digital twins is the development of (virtual) complex systems, utilizing a mass of data. This type of modeling would simply have been impractical even a few years ago. The further integration of digital twins into field tests and field test planning is likely to be one most interesting 2024 trends in digital agriculture.

Agmatix CEO Ron Baruchi explains the role of synthetic data field trials and how it can be leveraged to enhance the performance of digital twins.  

“Generating real-world data is an expensive, time-consuming process. It typically takes more than 150 studies to register a new active ingredient. 

  • From 2010-14, it cost around $286 million to discover and develop a new crop protection product.
  • $47 million (approximately 16%) was budgeted for field trials.
  • It takes just over 11 years from the first synthesis to the first sale of a crop protection product. 

Synthetic data is based on real-world data that has been generated by a model that keeps the same statistical properties and connections between the different parameters of real-world data sets. Datasets can be fully synthetic, or partially synthetic, where synthetic data helps fill in any gaps in real-world data. 

Synthetic data is not a replacement for original data, but a secondary source—one that can significantly reduce the time, cost, and effort in obtaining original data. Which offers great potential in reducing the time and investment of bringing new agricultural products to market.

Synthetic data can also be used for R&D purposes. Scientists can create a “digital twin,” in which a computer takes real-world data to maintain its statistical correlations, and generates synthetic data to create a system that emulates real life.

In agriculture, you could create a digital twin of a field trial to test which variables, such as soil types and weather conditions, are necessary for a successful real-world field trial. This has huge implications for agricultural input suppliers like crop protection companies, who are required to manage large field trials to receive regulatory approval, or seed companies that rely heavily on experimentation to improve their seed genetics. 

Digital twins can also be used to fill in data gaps from real-world sets. If an equipment error or a remote sensor fails and data is missing, you can generate synthetic data based on statistical models to fill in those holes and provide a complete picture of the study. Or if data is missing in certain geographic locations due to a lack of research facilities, synthetic data can help fill in those absent areas.”

In agriculture, Digital Twins have the power to increase efficiencies in the development and validation processes for new innovations. With increased efficiency, efficacy, and safety, using Digital Twins for field trials can be a competitive advantage in the race to market. 

Agmatix software is designed to help companies overcome challenges related to using traditional field trials alone through advanced technologies like Digital Twins. With the end-to-end Agronomic Trial Management solution supporting organizations to plan, execute, and govern their agronomic field trials, companies can easily adopt advanced technology into their processes and reap the benefits of faster, more effective field trials. 

#3 Technical Innovation in Regenerative Agriculture

Trends in agriculture in 2024 will include greater technical innovation and research into regenerative agriculture. The essence of regenerative agriculture is mimicking natural processes and biodiversity (within a managed plan) on agricultural land. It encompasses a holistic approach to preventing and reversing soil erosion and improving soil health. 

Regenerative agriculture uses tailored hybrid solutions that can include adaptive grazing, the incorporation of cover crops, forage crops, and perennial grasses to vulnerable areas, along with a no-till planting plan, data-based fertilizer strategies, and an ecologically friendly approach to pesticide use. As we face the challenges of climate change, and the requirement to feed a world population of over 8 billion people, regenerative agriculture has never been more vital. 

The availability of accurate and up-to-date data enables the development of localized regenerative agriculture solutions that are tailored to soil conditions, weather conditions, and microclimates, current crop growth or land use, as well as individual budgets and local regulations. 

Agmatix is dedicated to fostering the widespread adoption of regenerative agriculture practices through rapid and effective means. Utilizing site-specific data, the Agmatix platform offers a holistic view of sustainability that extends well beyond simple carbon metrics and one-size-fits-all solutions. This approach encompasses a range of elements, including soil health, crop protection, and the efficiency of nutrients and irrigation, among others. By setting site-specific benchmarks, the platform enables the establishment of realistic, actionable objectives for growers, promoting scalable sustainability and formulating strategies tailored to local environments. 

Furthermore, Agmatix’s commitment to regenerative agriculture shines through its platform. It offers accurate, user-friendly tools for creating crop nutrition plans centered on sustainability. This empowers agronomists with resources to guide growers in adopting regenerative practices, which not only benefit the environment but also enhance productivity. 

#4 Managing Data with Advanced Cloud Solutions

Innovation in agriculture is often data-dependent and the cloud gives researchers the ability to collate, manage, and extrapolate information from data in a way that was simply unimaginable for previous generations of agronomists. According to IDC, agriculture is growing exponentially year over year, and it is estimated that by 2036 the amount of data collected on the farm will increase by more than 800%. An agriculture field trial data tool that utilizes secure cloud systems can give a range of stakeholders real-time access to relevant information that is harvested from a mass of data. Trial durations are reduced, costs are cut, and the volume and scope of trials can be increased. 

Cloud technology can be applied to every aspect of agriculture and food production, including crop management, crucial soil information, monitoring and analyzing crop growth over multiple seasons, planning new agricultural ventures, and leveraging local knowledge for decision-making. Cloud-based solutions enhance researchers’, agronomists’, and farmers’ abilities to collaborate and make real-time data-based decisions. 

Agmatix software is cloud-based to enable maximum efficiency, security, and collaboration. This game-changing technology has been key to Agmatix developing solutions for trial management and crop nutrition management that can be used in-season for time-sensitive decisions. 

For research and development companies, cloud-based technologies enable a complete overhaul of legacy processes to unlock new, efficient ways of conducting business. Cloud-based technology is cost-effective; reduces overhead, doesn’t require massive IT teams or hardware storage space, and it’s scalable to meet business needs. It also provides new ways of doing business, through easy collaboration with external stakeholders and automatic access to data that’s needed to make important decisions in the research and development process. 

#5 Innovation Across the Agricultural Spectrum

Agriculture has roots in innovation. In fact, shifting away from a hunter-gatherer lifestyle to an agrarian one was an innovation in and of itself! The earliest farmers were instinctive researchers and scientists who, through trial and error and observation, succeeded in producing a surplus of crops and ensuring the survival of each succeeding generation. 

Past innovations in agriculture were essentially practical and began with selective breeding, the use of fertilizers, the development of water collection and irrigation systems, primitive pest control methods, pollination techniques, and various food preservation and production techniques. As agriculture progressed, farmers adopted crop rotation, and the Industrial Revolution led to innovations like seed drills and steam-powered farm vehicles. 

The new technological revolution, combined with the shift towards sustainability and environmental protection has brought us to the threshold of what will likely be the fastest, most intense, and most transformative period of agricultural innovation in human history. Innovative trends in agriculture in 2024 will include progress in the development of hardy crop strains that can thrive as the climate changes, the identification and adoption of nutrient-dense ‘superfoods’, and a shift towards specialized agriculture in non-rural settings. 

Innovation at the farm level is poised for impact, too. Armed with digital technologies, farmers can improve the processing and use of the data they collect on the farm. Agtech solutions can help farmers and agronomists measure and demonstrate the real-life return on investment and value of agriculture technologies. 

As we face the pressures of climate change, challenging geopolitical events, and sustained population growth, the most important Agtech trends in 2024 will be those that increase innovation and shorten the time to market for game-changing new products. Companies that can plan flawless field trials with shorter durations, and deal proactively with regulatory and compliance requirements, will have a definite competitive advantage. McKinsey notes that technology can increase productivity which directly impacts the bottom line, saving 10 to 15% percent of overall research and development costs through tools like generative AI. 

Armed with the Agmatix Agronomic Trial Management solution, research and development companies can deliver innovations at a faster pace than ever before. Both a competitive advantage and a necessity to overcome challenges related to a growing global population and climate change, faster innovation is possible through adopting intelligent AgTech solutions.

Agmatix’s current solutions and their pipeline of AI and machine learning-enabled technologies will enable stakeholders across the industry to innovate faster than ever before. 

Join Agmatix in a Pivotal Year for Agtech

The year 2024 stands as a pivotal period for advancements in agronomic research and the innovation of agricultural products. The rise of Gen AI is a significant trend to watch and the impact of digital twins on field trials cannot be overstated. Additionally, cloud-based technologies are revolutionizing the Agtech landscape and are expected to significantly influence agroinformatics trends in 2024. At Agmatix, we are at the forefront of these developments, leveraging these cutting-edge technologies and crafting advanced software solutions that are reshaping the field of agronomy.

Agmatix will continue to strengthen its position as an AgTech market leader and will focus on bringing its advanced technical solutions to companies seeking shorter and more cost-effective field trials. Agmatix is equally committed to helping agronomists and their growers improve harvests and yields, reduce costs, implement regenerative agriculture, and branch out into new and profitable niches. 

Accelerating R&D with Field Trial Software

The Agmatix Agronomic Trial Management Solution is transforming the entire process of research and development. A suite of new technologies, combined in a single platform, can optimize agronomic trials, reduce costs and accelerate time to market for vital new products.

As we enter a new agricultural revolution, the current possibilities of research and development are arguably more exciting than at any other time in human history. Researchers and scientific institutes around the world are harnessing the latest technologies to achieve the goal of universal food security. 

The latest AgTech and related technologies are also helping agronomists to adapt to the new realities of climate change and extreme weather events while meeting public demand for sustainability, environmental protection, and ethical food production. 

The integration of new technologies like AI and machine learning, SaaS cloud storage, and new field research software is not restricted to new agronomic products. Recent technological advances have the potential to revolutionize the actual processes of R&D and how field trials themselves are conducted. Our new capacity to innovate and modernize within agronomic research, and to implement much faster field trials, is likely to facilitate a major leap forward over the next decade.

Agmatix´s Agronomic Trial Management Solution is designed to achieve and integrate the 3C’s of field trials: collaboration, collection, and compliance. The software enables fast and effective trial planning, enhanced data collection and management, improved stakeholder collaboration, and comprehensive regulatory compliance. The high-tech agricultural research management platform can substantially reduce time to market, as well as reduce R&D costs. 

Companies that use the Agmatix Agronomic Trial Management Solution can not only benefit from faster agronomic trials. When trial costs are reduced, there is a clear potential to conduct a greater volume of trials. Put simply, research budgets stretch further when trials are cheaper and shorter. Platform users can develop a clear competitive edge in the crop protection space, as well as in other agronomy markets. The advantages are obvious for all companies, but can completely transform the R&D landscape for startups and SMEs.

Trial Management Efficiency 

The quality of the initial comprehensive study design for agronomic trials can often determine whether the project remains cost-effective and concludes within a 

trial-to-market timescale that is acceptable to clients and stakeholders. The Agmatix Trial Management Solution makes comprehensive end-to-end planning simple and flexible. 

The platform design places a significant emphasis on user-friendly procedures and on using simple tools to achieve sophisticated tailored outcomes. The electronic notebook is a major innovation that saves considerable time for researchers and reduces the possibility of human error. 

The platform’s drag-and-drop capabilities also permit a faster and more intuitive workflow from initial layout design, through to execution and on to analysis and reporting. Researchers and trial managers can use the platform’s task management tools to maintain a constant overview of all aspects of a trial. Remote managing, monitoring, and controlling becomes a simple and secure process. The Agmatix Agronomic Trial Management Solution delivers a genuine next-generation study design capability. 

Shorten Time to Market with Enhanced Data Collection 

Enhanced data collection and improved reporting efficiency are at the heart of next-generation data driven agronomic solutions. The Agmatix Trial Management Solution standardizes data for every field trial via an advanced ontology hierarchy system and treats harvested data as a valuable asset that drives innovation and discovery. 

Improved data stewardship delivers both security and flexibility, allowing trial managers to set permissions and authorizations to suit each project’s needs. Risks are reduced through automatic identification of data collection issues and outliers. Databases are IP-protected and meet all regulatory compliance and industry standards. 

The underlying need to reduce time to market is met in part by customizable data collection templates and an electronic notebook. This completely eliminates the need for laborious manual data entry, as well as the difficulties of working with a variety of different file types, and units of measurement. 

Data collection is streamlined and harmonized throughout the platform and field research software. The mobile app gives users the option to work offline and continues to deliver precision data collection with no reduction in functionality or user experience. Reporting – including protocols, treatments, images, etc. – can be carried out seamlessly with just a few clicks. 

Inspire Stakeholders with Enhanced Collaboration 

Any field trial depends on the combined expertise and active participation of all its stakeholders. Timely contributions from subject matter experts and specialists are essential along the entire trial-to-market timeline. 

One of the challenges that field trial managers face is how to disseminate data (within the context of agreed permissions) and ensure that diverse teams, in different geographical locations, can work together in sync. Even when different teams are working on completely separate aspects of a field trial, they may need to perform their allocated tasks simultaneously to shorten the time to market.

The Agmatix Trial Management Solution makes seamless collaboration between stakeholders easy. The entire system of user authorization is logical and simple to implement and allows managers full oversight and transparency at all times. As soon as stakeholders have immediate access to trial data and to any relevant agronomic database, the pace of innovation rapidly increases. 

Field trial participants are typically highly motivated people who are passionate about making new discoveries and developing – and launching – new agronomical products. When they have real-time access to data, and the opportunity to channel their knowledge and creativity, the results can be amazing. A genuine collaborative effort, via a user-friendly interface, can rapidly accelerate time to market and increase the ROI for any field trial.

Cut Operating Costs from Trial to Market

R&D is essentially an investment and depends entirely on funding. In a corporate environment, R&D teams are competing with other departments for a share of the company budget. The ability to demonstrate cost-effectiveness and value for money can be vital when it comes to securing approval and funding for a new field trial. When trial planners and managers can demonstrably reduce time to market for profitable products, they are immediately on a stronger footing. 

Efficiently run field trials are invariably faster and more cost-effective. A combination of optimized comprehensive planning, top-quality field research software, enhanced data collection and analysis, and full stakeholder collaboration can drive field trial costs down exponentially. 

An important technical innovation that goes a long way toward reducing costs is the right cloud-based SaaS solution for data management. Cloud technology requires fewer additional expenses in the form of customizations, integrations, and patchwork software. 

Ownership is cheaper overall and the technology is more reliable. Crucially, data management (particularly the allocation of permissions) is more intuitive and less laborious. It is also simpler to achieve regulatory compliance from day one, eliminating the need for retroactive compliance measures and shortening the real duration of a trial. 

Develop a Competitive Advantage with Agmatix

The Agmatix Agronomic Trial Management Solution can transform how you conduct agronomic trials and deliver an improved ROI as your teams shorten the time to market for new products. The seamless integration of the 3 C’s of field trials: collection, collaboration, and compliance, results in speed, accuracy, and value for money. 

A shorter and more cost-effective R&D cycle translates into a competitive advantage that can grow exponentially. We are already entering a new, tech-driven agricultural revolution. Companies that embrace the latest technological innovations will be operating from a position of strength as they seek to expand their share of the markets. 

The Agmatix Trial Management Solution is a superb tool for agronomy researchers and innovators. It brings your teams and stakeholders together in real-time, via a secure user-friendly interface, and allows them to combine their energies and talents within a predefined structure. When obsolete data silos and time-consuming data management processes are eliminated, the results of focused collaboration can be awesome!

Agmatix is committed to meeting the challenges of delivering global food security and to protecting the environment by creating sustainable agriculture. The Trial Management Solution is a game-changing technology for researchers and agronomists who share our goals and are working to create a better future for the entire planet. We can transform how you plan and manage your vital field trials, accelerating R&D and significantly reducing time to market.

Try the Agmatix Trial Management Solution now!

AI based cloud tech in agriculture field trials

From push cart to F1 – shifting from on-premise field trial solutions to cloud-based AI

Push carts, also known as hand carts, have been around for centuries and were an early form of transportation. These carts are designed to be pushed by a person and are usually used to move goods or people for short distances. 

On the other hand, F1 cars are highly sophisticated cars designed for speed, agility, and precision. They are made of advanced materials such as carbon fiber and feature powerful engines, advanced aerodynamics, and cutting-edge electronics. F1 cars are built for maximum speed, cornering, and braking performance and are capable of reaching speeds in excess of 200 mph. Let’s dive into this analogy applied to agriculture.

On-Premise Technology Limits Speed & Distance 

As agriculture first began using technology, on-premise options were often the only choice. Many field trial researchers continue to use on-premise technology today. And while it gets the job done, it also adds limitations to innovation, growth, and speed. In many ways, on-premise technology can be compared to push carts, which are slow, require manual labor, and can only go short distances. Like push carts, on-premise technology can be limiting, as data collection is often manual, time-consuming, and prone to errors. The lack of scalability and limited access to data further restricts the potential for growth and innovation.

One of the biggest limitations of on-premise technology is data quality issues. Data collection can be incomplete, inaccurate, or inconsistent. The manual data entry process is time-consuming and error-prone, which can lead to costly mistakes.

Another limitation of on-premise technology is the lack of scalability. If a business wants to expand its operation, it may need to invest in more infrastructure, hardware, and software. This can be a costly and time-consuming process. It also limits the ability to access data from anywhere, as information is often siloed within a specific location.

Limited access to data is also a significant issue with on-premise technology. It can be difficult to share data across teams, departments, or even different locations. This means that valuable insights may not be available to those who need them, which can result in lost opportunities for innovation and growth.

In agriculture specifically, speed is of the essence, and decision-making must be fast. Delays could set an innovative solution back a year or more if the timing doesn’t match up with customer or research growing seasons. This is where cloud-based technology can help. By providing real-time access to data from any location, cloud-based technology enables faster decision-making, leading to increased efficiency, productivity, and profitability.

F1: Going the Distance

F1 cars are the pinnacle of transportation technology, designed to achieve the highest levels of speed, precision, and maneuverability. With their aerodynamic design and high-performing engines, they are optimized for pushing the limits of what’s possible on the race track. The technology in an F1 car is a far cry from the limited capabilities of on-premise technology. On-premise technology, like push carts, can be slow and cumbersome, with limited scalability and access to data.

In an F1 car, every element works together for a fully optimized machine. From the engine to the tires to the aerodynamics, every aspect is designed to maximize performance and efficiency. This level of integration is something that on-premise technology simply can’t match. On-premise solutions are often disjointed, with different tools and systems not working well together. This can lead to data quality issues, a lack of scalability, and limited access to data.

Overall, the evolution of transportation technology from pushcarts to F1 cars is a testament to the growth and innovation of human ingenuity. The same can be said for the shift from on-premise technology to cloud-based technology. 

As businesses continue to seek out more efficient and effective ways of storing and accessing data, cloud-based technology offers a far more advanced and streamlined solution. Just as an F1 car is a superior mode of transportation to a pushcart, cloud-based technology is the superior solution for modern business needs.

AI-based Cloud Tech Takes the Lead in Agriculture 

The benefits of cloud-based agriculture technology are now too great to ignore. Cloud-based AI tech in agriculture is revolutionizing the industry, enabling real-time data analysis, remote monitoring and management, and facilitating collaboration among stakeholders. This new approach to on-farm experiments is transforming traditional field studies into data-driven experiments that leverage the power of artificial intelligence.

Agri AI cloud tech is particularly useful for monitoring crop health and growth, predicting yield, and identifying the best time to harvest. By using cloud technology, farmers and researchers can analyze data from a variety of sources, including soil sensors, weather stations, and satellite imagery, to make informed decisions throughout the crop growth cycle.

One of the key advantages of AI-based cloud tech in agriculture is that it allows stakeholders to work together in real-time, regardless of their location. This is especially important for field trials, where researchers may be spread out across different locations. With agri AI cloud tech, researchers can collaborate on experiments and share data in real-time, leading to faster results and more efficient research.

The role of cloud computing technology in agriculture fields cannot be underestimated. By leveraging the power of artificial intelligence and cloud-based technology, the agriculture industry can optimize research for the best performance, just like an F1 car on the track. The benefits of cloud-based AI technology are clear and will only continue to grow as more farmers and researchers embrace this new approach to agriculture.

Technology Enables Society to Grow 

In the same way that an F1 race car represents the pinnacle of modern engineering, cloud-based technology has revolutionized the agriculture industry, enabling it to keep pace with the demands of a growing world.

The ability to access real-time data and insights from anywhere has opened doors to new resources and connections, spurring innovation in every aspect of agriculture, from crop management to supply chain logistics. AI-based cloud technology has proven to be a game-changer in on-farm experiments, providing farmers with the ability to remotely monitor and manage their fields, optimize crop yields, and mitigate risks such as pests and weather events.

Just as F1 cars optimize research in the automotive industry for the best performance, agri AI cloud tech has optimized research in agriculture for the best performance, allowing for faster, more efficient, and more sustainable farming practices. 

With cloud technology and artificial intelligence, field trials can be conducted with unprecedented accuracy and efficiency, enabling researchers to gather and analyze data in real-time, and collaborate with stakeholders from around the world. The result is a more connected and collaborative agriculture industry, with the potential to transform the way we produce, distribute, and consume food.

Agmatix Enables Agriculture to Grow

Agmatix is a technology company that is making waves in the agriculture industry with its cloud-based AI solutions. Our platform offers advanced agri AI cloud tech solutions that are designed to accelerate research and innovation. The platform is built on cloud technology, which allows for ongoing improvements, enhanced security, scalability, and easy configuration. 

Additionally, the cloud-based architecture enables reliable backups and recovery of critical field study data, ensuring that researchers can access their data from anywhere in the world.

Agmatix’s Agronomic Field Trial platform is designed to support researchers and agronomists in collaborating to speed time to market, decrease costs, and ensure data accuracy. Agronomic Trial Management is an agricultural research management platform that provides holistic support across all steps in field trials. 

It’s easy to plan, manage, execute, and analyze multiple agricultural field studies and engage collaborators to make decisions efficiently. From drag-and-drop layout planning to customized treatments to data collection that integrates into the workflow, the Agronomic Trial Management platform is designed to make research and development seamless. 

The platform also enables researchers to conduct experiments in the field and gather data in real time, which can be analyzed using artificial intelligence. This allows researchers to identify trends and patterns quickly, which can be used to optimize crop yields, increase efficiency, and reduce costs. The platform’s mobile capabilities extend to supporting key steps in on-farm trials, too. These capabilities are possible because the platform is built on a cloud technology foundation.

With the Agmatix platform, researchers can work together remotely, sharing data and insights in real time. This collaboration helps to speed up the research process, enabling researchers to get products to market faster. Additionally, the platform ensures data accuracy by automatically collecting and analyzing data, reducing the risk of errors that can occur with manual data entry.

Agmatix’s cloud-based technology enables critical growth to address major challenges the agriculture industry faces: reaching net zero, addressing food scarcity, and feeding a growing population with fewer resources. Efficiency will be critical to delivering solutions that can make a difference while there is still time. 

Like Formula 1 cars, cloud-based AI field trial solutions speed across the finish line and deliver efficient, optimized results when it matters most. 

The AgriTech Evolution: The Past, The Present, and the Future 

Agriculture has always been a vital aspect of human civilization, providing sustenance and nourishment for generations. Over the years, technological innovations have helped transform traditional farming practices into a more efficient and sustainable approach. The evolution of agricultural technology, or agritech, has played a significant role in shaping the industry, from the early use of hand tools to modern-day precision agriculture techniques.

Agricultural technology can be compared to a tool kit that a carpenter uses to build a house. Just as a carpenter needs various tools to build a home, such as a saw, hammer, and drill, farmers also require different types of technology to improve their crop yields and protect their crops.

Over time, advancements in technology have enabled farmers to add new tools to their toolkit, just as a carpenter might acquire a power saw or pneumatic nail gun to improve efficiency and precision. Today, farmers have access to a vast array of technology tools, including drones for crop monitoring, soil sensors for precise nutrient management, and machine learning algorithms for predicting crop growth and pest infestations.

Just as a carpenter’s toolkit evolves over time, so does the farmer’s technology arsenal. With each new innovation, farmers can continue to refine their methods, optimize their yields, and improve the sustainability of their operations.

The Past: The Evolution of Agritech

Though hand tools and basic plows don’t feel innovative to us today, in the early days of agriculture, the invention of these types of tools made agriculture far more efficient. These tools allowed for the clearing of land, cultivation of crops, and harvesting of food on an increasing scale. 

The development of the self-scouring plow in the early 19th century was a significant advancement in agricultural technology. This plow allowed farmers to cultivate more land and plant crops more efficiently. The self-scouring plow was designed to prevent soil from sticking to the blade, which made it easier for farmers to till their fields.

In addition to the self-scouring plow, other agricultural innovations during this time period included the reaper, which helped farmers harvest crops faster, and the seed drill, which allowed for more precise planting of crops. These innovations paved the way for increased productivity and efficiency in agriculture.

During the Industrial Revolution of the late 18th and early 19th centuries, agriculture began to undergo significant changes. Advancements in machinery and power sources enabled farmers to till, plant, and harvest their crops more efficiently than ever before. Instead of relying on manual or horse-drawn labor, farmers could now harness the power of steam engines and other technologies to automate many of their tasks. This revolutionized agriculture and set the stage for further advancements in the years to come.

The late 20th century saw the rise of the Green Revolution, a period of intense agricultural innovation and growth. This movement focused on increasing crop yields and improving food security through the use of advanced plant breeding, fertilization, and irrigation techniques. The Green Revolution had a profound impact on agriculture worldwide, helping to feed billions of people and improve the lives of millions of farmers and their families.

Throughout the 20th century, technology continued to play a crucial role in shaping agriculture. From tractors and combines to early GPS-enabled planting and harvesting equipment, farmers have always been eager to adopt new technologies that can help them work more efficiently and sustainably. This marked the beginning of a new era in agriculture, as the focus moved from bigger, faster, and more horsepower to being more efficient with the inputs at hand. A shift from singular focus on productivity to a focus on productivity through precision. 

The Present: AgriTech Development 

Present-day developments in agritech have revolutionized the farming industry. One such advancement is precision agriculture, which refers to the use of technology to optimize crop yield and reduce inputs. The use of GPS technology is a key component of precision agriculture, allowing farmers to accurately map their fields and apply inputs more efficiently. This approach helps farmers minimize waste, reduce costs, and improve yields.

Precision ag is fueled by advancements in many areas. Drones can provide farmers with high-resolution images of their fields, allowing them to identify potential problem areas and take corrective action. Additionally, variable rate technology (VRT) is now commonly used to apply fertilizers, pesticides, and other inputs more precisely, based on real-time data and analysis. VRT has a strong return on investment for farmers and reduces the amount of inputs applied, thus minimizing potential environmental impact. 

Several factors are driving these developments in agritech, including the need to feed a growing population sustainably. With the global population expected to reach 10 billion by 2050, it is crucial that farmers produce more food with less land, water, and other resources. Precision agriculture enables farmers to optimize their land use, reduce waste, and increase yields, all of which are critical to meeting the demands of a growing population.

The benefits of present-day agricultural technology are many. For one, farmers can now apply fertilizers more precisely, reducing inputs and minimizing waste. This not only saves farmers money but also benefits the environment by reducing the amount of nutrients that leach into groundwater or runoff into nearby waterways. Additionally, precision agriculture allows farmers to identify potential pest problems early, reducing the need for pesticides and other inputs.

Precision agriculture, GPS, drones, and variable rate technology are all examples of present-day advancements in agriculture that are helping to meet the challenges of feeding a growing world sustainably. These technologies allow farmers to optimize their inputs, reduce waste, and increase yields while minimizing their environmental impact. The benefits of these technologies are clear and will continue to play a critical role in the future of agriculture.

The Future: AgriTech Accelerators

The opportunity for agritech to develop is not over – and neither is the need for new advancements. A recent McKinsey study found that leveraging technology to drive a select group of production practices has the potential to reduce greenhouse gas emissions by nearly 20 percent by 2050.

The opportunity hasn’t gone unnoticed, either. According to a report by Grand View Research, Inc., the global precision farming market is expected to reach USD 24.09 billion by 2030, with a projected Compound Annual Growth Rate (CAGR) of 12.6% during the forecast period. Cloud-based software model is expected to capture a significant market share, owing to its ability to lower energy consumption, offer ample data storage, and enable cost savings.

Increasing investment in the industry will support agritech accelerators that will further revolutionize how farmers produce crops and care for the environment. Digital agriculture, fueled by big data, will bring artificial intelligence to the industry to enhance decision-making. 

Predictive models will help inform decisions for the best yield and environmental outcomes. And artificial intelligence can even help farmers to execute in-field activities in a more sustainable way, such as spot-spraying AI-identified weeds instead of broadcast spraying the whole field. 

Cloud-based technologies are a key agritech development because they provide greater flexibility and drive innovation. With cloud-based solutions, farmers and agronomists can access real-time data from sensors and monitoring systems to make informed decisions about irrigation, fertilization, and pest control. 

The cloud also enables farmers to collaborate with experts and peers, sharing information and best practices to optimize their operations. Moreover, cloud-based technologies provide scalability and cost-efficiency, allowing farmers to adjust their resources and equipment to match the changing demands of their crops.

By leveraging cloud-based solutions, the agricultural industry can unlock new efficiencies and insights, leading to more sustainable practices and increased yields.

There is unlimited potential for some of the technology industries’ most advanced technologies to become agritech accelerators. In the food and farming industry, these technologies can make a meaningful difference in enhancing environmental protection and conservation and reducing food scarcity. 

Agmatix: Tomorrow’s Tech, Today

As agriculture evolves and new technology becomes available, new challenges also become part of the equation. This means that farmers and industry professionals must adapt and innovate to stay competitive and sustainable. In recent history, challenges such as managing big data, overcoming data silos, and the need for faster innovation have become prevalent. These challenges, if not handled, can undermine important new technologies. 

Agmatix is focused on enabling future digital agriculture technology by overcoming these challenges and providing holistic solutions to some of agriculture’s biggest challenges. This work enables faster innovations and makes next-generation technologies available to the industry today. 

The Agronomic Trial Management platform provides an end-to-end solution for efficiently managing field trials, ultimately leading to faster time to market and increased innovation through enhanced collaboration. Managing the critical field trial step has never been easier or more seamless. From layout planning to task management to data analysis, the Agronomic Trial Management platform provides next-level support. Mobile capabilities extend the value of the platform even further to on-farm experiments. 

Digital Crop Advisor takes crop nutrition recommendations to the next level. Keeping sustainability at the forefront, this data-driven decision support system provides automated, customized crop nutrition plans that take global and regional plans into account. Digital Crop Advisor makes it possible to balance yield potential and sustainability and understand potential tradeoffs between the two. 

The platform makes it seamless to evaluate product performance and product sales. Digital Crop Advisor is a next-generation technology that uses agronomic big data to support productive, sustainable crop production. 

Insights and models provide data-driven predictive insights utilizing artificial intelligence to analyze aggregated and standardized data. The value of field trial data can be fully unleashed as it’s easily turned into powerful agronomic insights and impactful crop models. Pre-built analytical widgets support statistical analysis of field trial data without any coding required. 

The backbone of these technologies is next-level data standardization and harmonization. Axiom technology breaks down data silos and harmonizes data – even legacy data – to unlock maximum value from agronomic big data. Data ingestion and fusion across all datasets allow users to leverage insights in powerful cross-trial analysis. 

Innovations in Agritech for the Future 

Overall, the history of agritech development is a story of innovation, adaptation, and growth. As the world’s population continues to expand, it will be more important than ever to continue pushing the boundaries of what’s possible in agriculture. With each new advancement, we move one step closer to creating a more sustainable, secure, and prosperous world for everyone.

Agriculture has evolved from diesel engines to data engines in a short time. There’s so much opportunity to build on today’s technology foundation and build even more innovations in agritech. Agriculture will feed a growing population in a resilient way that protects the Earth and natural resources, and Agmatix innovations will utilize cutting-edge technologies to make this possible. Agmatix is at the forefront of next-generation technologies, making tomorrow’s solutions available today. 

Unleashing the Power of Cloud-Based Solutions: Elevating Operational Excellence in Agronomic Trials 

Picture this: 

You’re a CRO that just landed a new client: an input company looking for crop protection research in support of a new potential product. You’ve been tasked with conducting field trials in different locations around the globe to test for marketability in those geographies and to collect the necessary data for regulatory approval. You’ll be planning and conducting the trial and doing all associated data analysis, creating the dossier for the regulatory agency, and supporting regulatory affairs efforts. 

You put your best team on the job, including a top-notch research scientist, numerous experienced agricultural technicians, a quality assurance manager, and a data analyst with years of experience. Your technical writer has written thousands of dossiers over the years. Even your field technicians are some of the best in the business – you’ve put together an A-team to make sure you nail this work. 

Your research scientists and agricultural technician start planning the trial, creating detailed trial protocols and treatment tables of different options, and gathering feedback from the client and the global team. The client is referencing past trials and past trial data, but when they share the data with you, it’s in a format that’s difficult to analyze within your current system because the categorization is different from your own standards. 

After much back and forth the team finally nails down the trial protocol and sends it to the client to review. The client approves it and emphasizes that they want to be in the loop throughout the entire trial to ensure protocols are followed and the data is collected correctly. 

Your team gets to work. But soon, it seems that there’s confusion about the protocol. All of a sudden, you’re scheduling conference calls and trying to track down tasks, and helping the team plan out the day-to-day execution to ensure the client is satisfied with the trial performance. 

The agricultural technicians begin the data collection process, and all seems to be going well. Eventually, the client starts asking for reports on the status of the trial and the data collected so far. 

So, the research scientist and agriculture technician start working with the project manager to define reports that meet the client’s needs. The first time they attempt to run the report, it takes multiple days to compile all the data from the different systems and sources! That doesn’t even include the cross-trial analysis of legacy data. And exporting the reports is another issue entirely. 

While this reporting is happening, the research scientists notice a series of issues in the data. Some is missing from certain trials – some manual data, and some collected in differing systems. They’re also finding outliers and struggling to standardize data and data types. 

The client is becoming frustrated with the time it’s taking to get things done. Your team is struggling to make all the different systems work – the systems for planning, the systems for operating the trial, and the systems for data management. 

If this situation sounds familiar, it’s because it’s not unheard of. CROs are often stitching together multiple systems and numerous data types between what’s available to their company and what’s required by the client. This process can be time-consuming, frustrating, and sometimes even a total barrier to success. 

It’s time to put away the needle and thread and stop patching together systems to make a trial run. With cloud-based solutions vs legacy software, CROs and sponsor companies can run seamless trials focused on operational excellence and high-quality data analysis.

Legacy Solutions in a Patchwork 

Today, a field trial might require one system for planning the trial – selecting a design, optimizing for the geography, identifying treatments, and more. These systems aren’t always user-friendly and require a high degree of experience to use. 

The trial might require a project management tool, too. Depending on the size and scope of the company and trial, this tool can be used to manage tasks, check in with team members, and even overcome language and time zone barriers. 

Data collection often requires multiple systems. From complex automated data collection systems to mobile data collection that can be challenging in certain environments or lighting to pen and paper style data collection, all that information must be centralized, standardized, and aggregated. All of these different systems and file types have to be connected for analysis. Often, data analysis itself requires a unique software solution. 

Reporting to customers or providing internal visibility can require yet another system or series of systems to visualize data and make it understandable. 

These many systems and file types create efficiency challenges. Manpower is necessary to manually handle data, creating room for human error and requiring hours of work. Collaboration becomes challenging when stakeholders and clients can’t access the information they need on the timeline they need it, hindering decision-making and complicating necessary teamwork. 

Cloud Computing in Agriculture Streamlines Processes 

Cloud computing in agriculture has a lot of promise in a lot of areas. From on farm experimentation to global CRO-led field trials, cloud computing, and cloud-based platforms offer end-to-end capabilities for streamlining processes and increasing efficiency. 

Cloud-based agronomic solutions avoid the legacy format requiring files to be manually shared amongst collaborators. With cloud-based platforms for agricultural applications, all team members can access data – often even in real time. Collaboration and decision-making can happen faster when data visualization and reporting aren’t an arduous manual process. 

Cloud-based platforms for agronomic field trials can be the singular platform that includes all the capabilities and functionality needed for executing a complex field trial or farm experiment. From planning to management to data collection and analysis, only cloud computing can provide the access and capabilities needed to create an end-to-end solution. 

In the scenario above, you can imagine having a single system to share within and outside of the organization that works wherever trials are conducted. The solution covers data collection and storage from the first trial to the most recent trial, creating a warehouse of data that’s a single central source of truth. It’s possible to analyze and report on this data, creating single-trial or cross-trial analyses. 

And all of this is possible without integration projects and IT professionals spending hours building singular, centralized data views. 

Agmatix & Cloud-Based Agronomic Solutions 

Agmatix is a global company developing solutions to grow data for impact. Its Agronomic Trial Solution is one of the company’s data-driven agri solutions built on cloud computing. 

Agronomic Trial Management is designed as an end-to-end cloud-based system that supports every step of the trial process. Trial designs come together easily and quickly with drag-and-drop functionality. Hundreds of treatment combinations are available. And once the trial is ongoing, research scientists, trial coordinators, and field technicians get full visibility and control of the trial and related resources. Stakeholders can always be up-to-date on the trial status. 

The system is built to enable communication between all stakeholders, the team executing the trial, and clients. Agronomic data is accessible and shareable to the people who need it – even people who are partners outside your organization. 

Data collection, once a particular pain point for patchworked systems and file types, can be seamless. With a digital notebook, high-performing mobile data collection, and real-time results, you can be confident in the quality of the data and move efficiently towards putting it to work. 

Cloud-based agronomic solutions create efficiency gains, increase data integrity, increase innovation, reduce risk, and create competitive advantages as companies can move to market faster. The end-to-end capabilities of Agmatix’s Trial Management System help CROs and companies to execute seamless and efficient trials. 

The 3 C’s of Field Trials: Collaboration, Collection, Compliance

The Agmatix Trial Management Platform is transforming how vital field trials are conducted, shortening the time span between trial design and product release, cutting trial costs, and harnessing next-generation technologies to revolutionize data management.

Agronomic field trials can be uniquely complex projects that require skilled planning and comprehensive design, as well as the active collaboration of a variety of stakeholders and participants. The complexities increase when field trials are conducted in suboptimal conditions such as remote locations or on marginal lands, especially when they require real-time input and coordination from teams in different geographical locations and time zones. 

Ensuring that field trials reach their full potential while remaining within budget and on schedule, is a major challenge for trial managers. Running a successful trial requires three key components: collaboration, collection, and compliance. 

Achieving the 3 C’s of field trials has traditionally been challenging and time-consuming, and placed limitations on the scope and viability of trials. Using next-generation ag data analytics allows researchers to gain deeper insights into their experiments’ progress and outcomes. 

Agmatix launched the groundbreaking Trial Management Platform precisely to address these issues, utilizing newly available mobile technology, SaaS cloud data technology, AI, and machine learning. The platform literally transformed the ability of users to design and implement field trials, as well as their ability to standardize trial data and manage access to that data across multiple teams. 

The Trial Management Platform’s latest version updates host new features and upgrades. It incorporates the latest technological advances, as well as user feedback from research institutes, agronomists, farmers, and other stakeholders who successfully used the original version of the platform during field trials. The updated agronomic trial platform from Agmatix is user-friendly, and flexible, and allows flawless integration of the 3C’s of field trials. 

Enhanced Collaboration for an Optimal Outcome

A field trial is a complex collaborative process that requires the expertise and oversight of a variety of stakeholders and clients. With modern technology, the participants and clients in a field trial can literally communicate across continents, time zones, and linguistic barriers. 

Enhanced collaboration, with the full, timely, and active participation of every trial member and associate, requires a high-tech approach.  Field trial managers need a suite of tools that connects project participants to both trial and archived data and to each other, in real-time and via a single platform. Unnecessary (or obsolete) data silos and the isolation of remote teams are major obstacles to efficient and successful field trial outcomes.

Trial administrators invite trial members to participate and have access to the relevant data which enables them to receive the relevant data and contribute to the trial according to their fullest professional capacity. Researchers, agronomists, and other trial participants have all the tools to conveniently view, analyze, and report on the collected (and standardized) data, regardless of their actual geographical location.

The Agmatix Field Trial Platform effectively empowers its users. Stakeholders across the entire spectrum of a project can monitor field trial progress in real time and draw invaluable insights from the collated data. The platform technology is not only expediting agronomic research but has the potential to increase the number and breadth of future field trials.

Next-Generation Data Collection for Informed Decision-making

Field trials generate a mass of data. Even a basic research project can yield complex information about the performance of crop nutrients, pest control solutions, soil quality and composition, seed germination rates, the health and growth rate of plants, crop yields, etc. 

A common pain point in many field trials is the actual process of data entry. Previous generations of researchers and field workers were constrained by the limitations inherent in manual data entry. The processes were laborious, time-consuming, and vulnerable to human error. 

A complicating factor was the preponderance of differing data formats. A lack of data standardization created barriers to speed and accuracy during field trials. The challenges of effective data entry placed an additional burden on researchers responsible for devising comprehensive plans for new research projects. The updated Agmatix Agronomic Trial Solution completely transforms and streamlines data collection, revolutionizing this core aspect of agronomic research. 

Agmatix field trial management platform users receive a new level of data collection functionality. An electronic notebook and customizable data collection templates allow researchers to create sophisticated tailored data solutions. The data tools are advanced but are designed to be completely user-friendly and simple to master.

Users can generate customized reports – including protocols, treatments, and images – with just a few clicks. The Agmatix technology collects and compiles data from multiple locations, and then presents it for immediate viewing, analysis, and reporting. 

Transforming Data Collection for Crop Protection Research

Some of the most important field trials relate to crop protection. The ability to protect harvests and ensure good overall plant health and yield is key to achieving global food security, particularly as we face the challenges of global warming and changes to crop predation patterns. 

The Agmatix Trial Management solution is ideal for crop protection field trials, bringing new levels of efficiency and real-time control. Users can easily leverage electronic data capture and can easily assign, track, and monitor field assessments. The updated Agmatix platform transforms the documenting of treatments, sampling of events, and recording of observations into a simple and intuitive process. 

Data collection and analysis can be completed in a fraction of the time that was required for previous generations of studies. The mobile app also allows users to collect data while offline, a significant enabler for effective field research. All authorized participants can closely monitor the performance of a variety of methods of crop protection and pest management. 

As with other types of field trials, the advanced platform allows users to easily create tailor-made reports on the efficacy of different crop protection solutions. Comprehensive reports can encompass any range of treatment protocols, images, and required metrics. The entire process is streamlined, transparent, and geared towards allowing informed decision-making.

Meet Compliance Requirements From Day One

Regulatory compliance has emerged as one of the pillars of agronomic research. A comprehensive field trial plan that integrates compliance requirements, and provides the tools for checking whether requirements are being met, can save both time and money. Too often, trial managers have to meet compliance requirements retroactively, extending the time lapse between the completion of a trial and the launch of new products. 

The new Agronomic Trial Management solution meets all relevant industry regulations with meticulous attention to detail, removing a major burden from researchers and trial managers. The SaaS cloud-based platform provides full data security and privacy, without impeding workflows or denying authorized stakeholders access to trial data. 

More than anything, the updated platform can provide trial managers and clients with peace of mind. When you know that you will have full compliance with data protection regulations and industry standards and that privacy, data capture, storage, and transmission requirements are met, you are free to fully focus on important agronomic research.  

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Agmatix: Technical Innovation for Agronomic Research

In the world of agronomic research, the integration of cutting-edge technology has revolutionized how we approach agricultural experiment monitoring and management. The Agmatix Agronomic Trial Management solution harnesses key technologies and flawlessly combines them in a single platform. Users can integrate the three C’s of field trials: collaboration, collection, and compliance from the moment they begin to plan a new field trial. 

The Trial Management solution has a simple purpose – to help users and clients get to market faster. There is also a clear potential to reduce the overall costs of creating and conducting field trials and to achieve optimal results through expert collaboration and teamwork in real-time.

Advanced features like the electronic notebook, standardized data, new platform language, SaaS cloud data storage, and the integration of AI and machine learning are vital game changers for researchers and agronomists. The offline functionality of the mobile app for data collection is a significant advantage at field level, while the integrated compliance mechanisms can transform the administration of a trial. 

The Trial Management solution is a flagship product with the potential to revolutionize how field trials are conducted. It aims to increase the validity of trial data and facilitate informed decision-making based on trial results. This benefits not only R&D organizations but also aids in translating trial results for an organization’s sales and marketing departments and planning.

Agmatix is committed to the achievement of global food security within a generation and is continuing to research and innovate across the wider spectrum of Agtech.  If you’d like to work with Agmatix and contribute to innovation in agronomy and food production, we’d love to hear from you.

CROs Can Count on Agronomic Data Analytics Tools

Customer service holds paramount importance for CROs (Contract Research Organizations). Although advanced agronomic data analytics tools may appear to be primarily the concern of the sponsor (client), they actually serve as the cornerstone for exceptional customer service and operational efficiency for CROs operating in the agriculture industry.

CROs can utilize data and analytics tools to enhance communication and collaboration with their clients. By leveraging these tools, they can showcase their expertise in regulatory efficacy studies and fine-tune their services to provide the desired flexibility and reliability that meet their client’s specific needs.

Data and analytics tools can also be used to improve operational efficiency. For example, CROs can use these tools to track key variables and data integrity and optimize trial management. This can help CROs to reduce costs and improve efficiency, which can lead to increased profits.

In the agriculture industry, data and analytics tools are crucial for CROs. They play a vital role in supplying the required data and trial documentation for regulatory agencies to properly review product registrations. Additionally, these tools enhance customer service, operational efficiency, and profitability, making them essential for CROs’ success. 

Increasing Operational Efficiencies

Data analysis systems provide CROs with a comprehensive view of the trial data, which enables them to streamline their operations and improve overall efficiency. This allows them to identify areas where they can improve their processes, such as by automating repetitive tasks or optimizing resource allocation. Additionally, when their client, the sponsor, has changed to a protocol or trial task, these can be implemented in real-time. 

With Agmatix’s task repetition feature, CROs can easily replicate specific tasks and protocols across multiple trials or locations. By saving task parameters and inserting them into other trials as needed, the system ensures consistent task execution throughout all required trials, saving valuable time for trial administrators. Additionally, if the CRO or sponsor needs to slightly tweak a replicated task to meet the regulatory requirements of a specific region where a trial is being conducted, they can easily edit and save the changes, ensuring compliance and flexibility in trial management.

Additionally, by harnessing the power of advanced data analytics and robust analysis tools,  CROs can optimize resource allocation. This heightened transparency not only enables them to identify which resources are being used most effectively but also empowers them to strategically allocate personnel and assets to specific trial locations. This targeted resource allocation is fortified by a comprehensive understanding of trial mapping and personnel responsibilities, facilitating streamlined decision-making and efficient trial coordination. Ultimately, data analysis systems can enhance workflow management by providing CROs with a clear view of their workflow and identifying areas where bottlenecks are occurring and enabling proactive adjustments. This can help CROs to improve the overall operational efficiency of their operations.

Agmatix’s Agronomic Trial Solution makes it possible to effortlessly assign and track field assessments, document treatment tables, protocols, and capture all sampling events. 

Enhancing Data Collection and Validation

Agriculture data analysis is built on a bedrock of quality, high-integrity data that captures critical trial information as well as integrated data layers such as weather conditions. Efficient data collection makes this process seamless, and the right agricultural data management software can make data validation just as easy.

Advanced agronomic data analysis tools offer enhanced flexibility at the field level by enabling mobile data capture capabilities for precise data collection, even in offline environments. Agmatix’s Trial Management solution also includes a digital trial notebook for capturing relevant field observations in real-time through text inserts, photos, or videos. This eliminates the need for transferring pen and paper records or uploading photos and videos from other devices, ensuring seamless and instant data collection for more efficient trial management.

With advanced agronomic data analysis tools like the Agronomic Trial Solution, analytics can be used to standardize data collection protocols. Setting and monitoring protocols become effortless, and automation is a possibility. Through vigilant outlier monitoring, errors in data can be minimized, ensuring data accuracy becomes inherent and the trial’s integrity is guaranteed. This support enables the ultimate objective of providing necessary trial data to aid sponsors in bringing their products to market and complying with regulatory requirements.

Adhering to Protocols and Providing Accurate Reporting

Data analytics tools help CROs adhere to experimental protocols and regulatory requirements by providing a way to track and monitor data throughout the entire trial process. This includes ensuring that data is collected and recorded accurately, that it is compliant with all relevant regulations, and that it is reported in a timely and accurate manner.

Data analysis systems can be used to ensure data integrity which ensures data is collected in the required manner that is governed by the protocol and that the collection task is completed and reported in the timeframe which has been assigned. Real-time data visualization enables the trial admin and sponsor to view results immediately. This can help identify errors, outliers and draw conclusions.

Data analytics can be used to track compliance by monitoring the adherence to protocols and data documentation CROs can be confident that Good Experimental Practice (GEP) standards are met. 

Data analytics can be used to generate accurate reports by providing a way to summarize and analyze data in a clear and concise manner. Trial reports are entirely customizable, tailored to the sponsor’s specific requirements, and exported as .docx files. Further customization can be effortlessly completed, ensuring each report contains all the necessary information to meet the needs of both the sponsor and the regulatory agency.  In addition, the reports include trial analysis summaries, which facilitate trend identification and empower sponsors to make informed decisions regarding study design, execution, and effective communication of results to stakeholders.

Our Agronomic Trial Solution is an agricultural data management software that enables reporting steps with efficiency and ease. CROs can generate customized reports including information about protocols, treatments, and even images for stakeholders in just a few clicks. The platform also effortlessly collects and compiles data from various locations, making it immediately accessible to stakeholders for viewing, analysis, and reporting. Data can be exported into several formats, including chart images. 

Improving Customer Service

Agronomic analysis software can play a big role in improving customer service. The CRO Project Manager or Study Director can easily coordinate with sponsors and provide them with the insight needed. Agricultural data analysis of trial results can be carried out by CROs, offering a strategic differentiator for sponsors. This can potentially accelerate R&D cycle times and expedite product entry into the market.

Communication with clients is key, and finding a method to communicate timely updates with sponsors in an efficient manner supports both operational efficiency and customer service. Data analysis systems that provide efficient reporting allow CROs to provide real-time updates so sponsors are always “in the loop.” 

When customer queries arise, the CRO team has immediate access to the data, eliminating the need for time-consuming manual work like downloading and sending data to the sponsor. Alternatively, with Agmatix, CROs can add the sponsor as a user admin on the trial, granting them permission and direct access to the data, as well as other essential trial information such as protocols and tasks. This streamlined process enhances collaboration and responsiveness between CROs and sponsors.

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Ensuring Data Security and Confidentiality

Data security and confidentiality are of utmost importance to safeguard customer requirements and comply with regulatory standards. Implementing robust measures to protect sensitive information ensures trust and peace of mind for both customers and regulatory bodies. Data analytics tools have to have the appropriate mechanisms in place to protect customer data and intellectual property. 

Fortunately, end-to-end systems like Agmatix are specifically designed for agricultural data analysis, offering a fully secure and centralized repository. Unlike scattered notebooks and multiple software platforms that require management and tracking, Agmatix provides a comprehensive solution that simplifies data storage, and access, and ensures data security and integrity throughout the trial process.

Agricultural big data analytics systems like the Agronomic Trial Solution prioritize data protection measures, including data integrity and confidentiality. Agmatix’s Agronomic Trial Solution is designed with regulatory compliance in mind. We understand the importance of data security and privacy, and our solution ensures that data capture, storage, and transmission meet all necessary standards. Your data is protected and accessible only to authorized personnel by using our secure cloud-based SaaS platform.

Your research services can be greatly enhanced with the right advanced agronomic data analysis tools. CROs can expect increased operational efficiency, better data integrity validation, ensure adherence to protocols, experience accurate reporting, and deliver enhanced customer service. These capabilities provide holistic support for meeting operational and client-focused goals. 

Agmatix’s tools go beyond the average digital trial data tool. They provide end-to-end support to streamline the entire process. The Agronomic Trial Management solution was built with compliance in mind. CROs can rest easy knowing they’re using a high-integrity solution. 

CROs have a big opportunity in front of them to unlock true efficiency and customer satisfaction through advanced agronomic data analytics tools. Grab hold of these tools now and pave the way to a profitable, efficient future. 

Agronomic Field Trial Compliance and Reporting with Advanced Tools 

Compliance and reporting are key steps in the journey to bring a new product to market. The growth of biological and chemical products can be influenced as much by the speed of regulation as by the speed of innovation. In many countries, regulatory hurdles are increasing the complexity of field trial studies and requiring additional expertise to meet requirements for entry into market. 

Essential to meeting those requirements are the reporting processes that ag input companies and CROs utilize. As the regulatory burden grows, so does the opportunity to build efficiency and ease into the process of capturing necessary field trial data and reporting it in the required format and timeframe. 

Utilizing advanced data capture and analysis tools is one step to making reporting for regulatory needs easy. But by utilizing a holistic agronomic field trial technology, ag input companies and CROs can streamline operations, enhance the efficacy of field trials, and compliance and reporting all with one tool. 

Agmatix’s Agronomic Trial Management solution is a comprehensive technology designed to support ag input companies and CROs as they plan, execute, and monitor regulatory field trials. It also provides advanced data capture and analytic capabilities to support the efficacy of field trials. Best of all, the solution is built to be fully compliant and support all aspects of the trial lifecycle.  

Easily Capture Required Trial Information 

The Agronomic Trial Management solution is designed to make regulatory field trial data capture as easy as possible. All required information can be captured in a centralized place. These values may include data that is typically captured manually, such as weather data. A mobile application makes it easy for everyone involved in the lifecycle of the trial to complete data collection taks and input trial data, even if they are offline. Treatment application and crop protocol data that are required for registration are also captured and ready for exporting to meet regulatory requirements. A dedicated information section includes EPPO values and standards. This same section enables documentation of the necessary instructions. 

The Agronomic Trial Management solution also includes csutomizable design models and treatment tables that were developed with crop protection trials – and the associated regulatory needs – in mind. The system seamlessly integrates intuitive trial design and data capture for products and active ingredients.

The solution is also designed for agronomic researchers to capture, store, and transmit data related to the necessary standards. Because Agronomic Trial Management is a cloud-based SaaS solution, data is protected and authorization protocols allow only authorized users to access it. Solution admins can manage these authorizations to align with the reporting structures and internal and external collaborators that are engaged inregulatory field trials. The solution can seamlessly integrate with internal systems, ensuring an effortless IT configuration.

Data Integrity Increases Confidence 

When embarking on the data reporting phase of a regulatory field trial, agricultural input companies seek assurance in the outcomes of their studies and the accuracy of the data they present. Utilizing the Agronomic Trial Management solution enables the realization of this goal. 

The Agmatix single-point data capture and storage solution means that spreadsheets and handwritten field notes are entirely eliminated. The user-friendly mobile notebook functionality enables the inclusion of pictures and videos as attachments, facilitating thorough and comprehensive note-taking. Without handwritten notes, physical notebooks, and multiple spreadsheets, users will eliminate risk and room for error. 

Real-time data collection enables immediate validation of data. Once a data collection task has been completed, outliers can be identified quickly and issues can be remedied before they negatively impact the entirety of the trial. 

Data integrity also comes from the chain of custody and protection of the data. This tool is cloud-native and the site is secure while also being agile with simple configuration. Data security, backup, and recovery are vastly improved over legacy systems. 

Agronomic Trial Management also allows for increased governance overall regulatory trial operations. With this level of protocol management, trial operators and everyone involved in R&D can be confident that the trial is executed as planned and the risk of human error is minimized. 

As a single, centralized trial documentation and management solution, Agronomic Trial Management ensures data integrity. 

Reporting for Regulations 

Meeting regulatory reporting guidelines and requirements can be a lengthy process. However, by leveraging the Agronomic Trial Management solution, the creation of trial result summaries and reports evolves from a cumbersome, multi-day process to one that is accomplished within a matter of hours.

Customizable capabilities for reporting enable researchers to find the best way to report comprehensive data for regulators. They can determine the right details for regulators and provide those without complex algorithms and data wrangling. 

Ag input companies and CROs will find that there are a number of capabilities within the app that make the shift from field trial data capture to data reporting an easy one. Data collection forms ensure that the captured data is consistent. The harmonized data can then be easily exported for regulatory reporting and compliance purposes. The Agronomic Trial Management solution can make preparations for regulatory reporting both easier and more efficient. 

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Beyond Compliance and Reporting 

Compliance and reporting are key steps in the field trial process. But, they aren’t the only factors an ag input company or CRO considers when adopting an agronomic field trial technology. Because Agronomic Trial Management was build to be fully compliant, users can spend less time worrying about compliance and reporting and more time focused on the features that enable operational efficiency and maximum data insight. 

Operational efficiency features abound in the most up-to-date version of the Agronomic Trial Management solution. Crop protection calculations such as plans for application and product rate per treatment are built into the solution to make execution easy. Trial reports for internal purposes, such as product efficacy data for marketing or further research and development, can be created easily. Results can be visualized and conclusions can be summarized quickly. 

An AI recommendation engine creates recommendations on everything from trial layout to results analysis. This functionality reduces cycle time and accelerates innovation as insights fuel discoveries and reduce risk for trial programs.

Collaboration between internal and external stakeholders is a critical part of executing a field trial study. The Agronomic Trial Management platform builds efficiency into the way users collaborate. Data is available to all stakeholders and both data and protocols can be shared among collaborators – even those that are external – within the platform. Gone are the days of sending files back and forth and worrying about version control. 

Analysis and insights are also seamless with the Agronomic Trial Management platform. Users can analyze the results from a single trial to get specific with the data. They can also complete cross-trial analysis to discover new insights from the inclusion of other trial data. Analysis can be customized and visualized to the specific needs of the company to gain the insights needed for decision-making. This revolutionary product enhances data analysis capabilities to unlock true value from data. 

Across the lifecycle of a field trial, the regulatory landscape is a consideration. For governments, scientists, companies engaged in research and development, and even for individuals in the agriculture community or general population, ensuring regulatory compliance builds confidence and enables innovations to make a real difference in everyday life. Compliance and reporting are a necessary step that’s made easier through cloud-based, next-generation technologies. 

Agmatix’s Agronomic Trial Management solution significantly enhances efficiency when it comes to regulatory reporting and compliance, providing crucial support to companies in accelerating their innovations to market. Notably, our solution has demonstrated a remarkable 20% increase in operational efficiency, streamlining key processes such as product development and registration preparation for a leading global crop protection firm. This proven platform is available now. Learn more at 

The future of agriculture: why commercial agriculture should adopt cloud technology

Technology Is a Driving Force in Agriculture Today

Agriculture has become a major adopter of technology to drive ROI and sustainability. Commercial agriculture needs to be quick and efficient with their operations to meet sustainability requirements and production goals in the current environment and the future.  Technology has helped farmers improve yields, reduce costs, and protect the environment. 

For example, drones are now being used to monitor crops, identify pests and diseases, and apply pesticides more precisely. Through this technology, farmers have been able to apply optimal crop protectants, which is good for the environment and for farmers. Additionally, technology is helping farmers to improve their efficiency. Precision agriculture tools are a good example of this as they are helping farmers to apply water and fertilizer more precisely, reducing costs and increasing environmental sustainability. 

Artificial Intelligence (AI) is reshaping the agricultural landscape with capabilities to drive innovation and optimize agricultural processes. AI-powered systems are capable of analyzing large amounts of data from a variety of sources. These datasets may include weather patterns, soil composition, historical yield data, and crop health information. Through the use of machine learning algorithms, AI has the ability to highlight patterns and correlations that humans may overlook. Ultimately, this leads to improved crop prediction and disease detection. The integration of AI in agriculture could drive increased efficiency but also sustainable practices by minimizing resource waste and environmental impact.

The agricultural industry has become a data-rich sector with the adoption of various sensors, satellites, and IoT devices. Big data analytics has emerged as a powerful tool in harnessing the vast amount of information generated from farms and agricultural operations. By collating and analyzing this data, farmers gain valuable insights into crop performance, soil health, and overall farm management. 

Predictive analytics based on big data enables farmers to anticipate challenges, optimize resource allocation, and develop more resilient farming strategies. Moreover, big data in agriculture fosters knowledge-sharing among farmers and researchers, creating a collaborative ecosystem that facilitates the exchange of best practices and innovative solutions. Harnessing big data in agriculture unlocks immense potential for sustainable and efficient food production to meet the growing demands of a rapidly expanding global population.

Agricultural field trial technology has significantly advanced over the years, revolutionizing the way farmers approach crop cultivation and research. Traditional field trials were time-consuming, expensive, and limited in scope. However, with the advent of advanced field trial technology, data management for field trials has become more streamlined. 

However, many of these solutions are still on-prem and are limited in scope and functionality. For the future of commercial agriculture, on-prem technology must be set aside and cloud computing has to lead the way. 

On-Prem Technology Barriers 

Today’s technology in commercial agriculture is largely on-prem, which is functional but comes with a set of limitations and problems. Of all the challenges created by on-prem technology, cost, scalability, security, and integration are all barriers to achieving next-generation performance. 

On-prem technology is expensive. When hardware and software are deployed within an organization’s physical premises and the organization is responsible for managing, maintaining, and securing that infrastructure, complexity, and cost is incurred. One of the primary expenses is the upfront capital investment required for purchasing and installing the necessary hardware and software, which can be substantial, especially for larger organizations with complex IT needs. 

Additionally, ongoing costs associated with maintenance, upgrades, and support contracts add to the financial burden. As technology rapidly evolves, on-prem solutions may also become obsolete faster, necessitating costly hardware replacements and software updates to remain competitive and secure. Furthermore, the need for skilled IT personnel to manage and troubleshoot on-premises systems contributes to the overall expenses.

Scalability challenges with on-premises technology pose significant problems for commercial agriculture organizations, with difficulties in accurately predicting future requirements leading to underutilization or costly upgrades, time-consuming provisioning and configuration of processes for sudden growth, and increasing complexity in maintenance and management as the IT infrastructure expands. Additionally, geographic scalability limitations can cause latency issues and reduced productivity for geographically diverse teams. 

Security challenges with on-premises technology present critical concerns for organizations aiming to protect sensitive agricultural data. One of the primary challenges is maintaining robust cybersecurity measures to safeguard against potential threats and attacks. As organizations manage their own infrastructure and data centers, they must invest in firewalls, intrusion detection systems, encryption protocols, and other security mechanisms to thwart unauthorized access. 

Moreover, ensuring timely and comprehensive updates and patches for software and hardware vulnerabilities becomes crucial to prevent exploitation by malicious actors. On-prem technology also demands vigilant monitoring and constant oversight to detect any suspicious activities or anomalies promptly. Additionally, the responsibility of physical security lies with the organization, necessitating measures to protect against theft, data breaches, and other physical risks.

The need to seamlessly integrate various on-premises systems and technologies can lead to data silos and hinder efficient information exchange. The lack of standardized communication protocols and the incorporation of emerging technologies like AI and big data analytics may strain existing infrastructure and hamper performance. Addressing these challenges requires careful planning and standardization.

Together, these problems pose significant barriers and are preventative of commercial agriculture moving quickly and being highly innovative – two things that the future will require. 

Cloud Technology: The Sky is the Limit 

Commercial agriculture and cloud computing go hand-in-hand. With advantages like low costs, scalability, ease of use, and ongoing improvements, cloud technology will enable commercial agriculture to meet future goals through speed to market and innovation

Cloud-based technology offers the advantage of lower costs and scalability. Unlike traditional on-premises setups that require substantial upfront investments in hardware and infrastructure, cloud-based solutions operate on a pay-as-you-go model. Organizations only pay for the resources and services they actually use, allowing for cost scalability based on demand. 

Additionally, cloud providers handle the maintenance, updates, and security of the underlying infrastructure, eliminating the need for dedicated IT staff and reducing operational expenses. The shared nature of cloud resources also enables economies of scale, further driving down costs for users. 

With cloud-based technology, agriculture businesses can access a wide range of services and computing power without the financial burden of owning and managing their hardware, enabling more cost-effective and efficient operations. Cloud-based technologies provide a more flexible and efficient approach to meet the dynamic demands of the business landscape.

Commercial agriculture will also benefit from ongoing improvements. Agribusinesses will be able to take advantage of new features, enhanced technologies, and efficiency-enhancing updates without having to acquire additional hardware. 

Cloud computing applications in commercial agriculture provide the opportunity for enhanced collaboration and easy configuration. With the ability to manage access to authorized users and have multiple collaborators engaged with the software at once, collaborators don’t have to wait for data or information and companies can make decisions more quickly. Cloud technology is usually very customizable to the needs of a specific commercial agriculture business, and can be configured as needed without complexity or dedicated IT staff. 

Cloud-based technology also offers increased security measures, providing robust protection against cybersecurity threats. Cloud service providers employ dedicated teams of security experts to continuously monitor and update their systems, ensuring the latest defenses against evolving cyber threats. These providers also implement strict access controls, encryption protocols, and multi-factor authentication to safeguard sensitive data from unauthorized access. 

Cloud platforms offer data redundancy and backup features, minimizing the risk of data loss due to hardware failures or natural disasters. The cloud’s distributed nature also makes it resilient to localized disruptions, further enhancing data availability and business continuity. Overall, by entrusting their data and applications to reliable cloud providers, businesses can bolster their security posture and focus on their core operations with confidence in the protection of their valuable digital assets.

The future of commercial agriculture and sustainable agriculture will need to be in the cloud to take advantage of these benefits of scale, lower costs, security, and additional collaboration. 

Agmatix, Cloud Technology, and Agriculture 4.0

Cloud computing applications in commercial agriculture will support the Agriculture 4.0 revolution which relies on digital technology to drive smart, efficient, and sustainable agriculture. 

New generation technology from Agmatix is all based in the cloud to optimally support commercial agriculture in growing data for impact. 

Agmatix’s Agronomic Trial System is able to deliver a holistic solution that supports the planning, management, execution, data collection, and data analysis of field trials because it’s cloud-based. This technology works like an agronomic database in capturing data in a single place and allowing multiple users to access and analyze it. The solution even includes a mobile application that’s enabled by the cloud and allows for data capture online and offline. 

Users will find efficiencies in data collection and trial operations while increasing data integrity and reducing the total cost of ownership of their field trials. Data collection issues, sensor defects, and outliers can be identified early in the trial process to reduce the risk of data integrity issues. At the end of the day, the platform is able to provide a competitive advantage to users who see shorter cycle times and increased efficiency in bringing new products to growers. 

The Digital Crop Advisor solution is a decision support system designed to support crop nutrient optimization through data insights and expert knowledge. Global yield and regional trends are key inputs to driving crop yield, testing product performance and even understanding and sustainability. 

Agronomists will use this digital, cloud-based tool to work with growers on an optimized nutrition plan to optimize yield and sustainability. Farmers will benefit from the mobile capabilities of the system for their on-farm experiments. Digital Crop Advisor is able to offer real-time decision-making and access to agronomic data because it’s built with cloud technology. 

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The Future of Ag Depends on the Cloud

Agriculture must address current and future challenges with speed and innovation, both of which are enabled through cloud-based technology. Cloud computing applications in commercial agriculture support agriculture companies in reaching goals around operational efficiency, innovation, research and development, and product performance in the market. Moving away from legacy or on-prem solutions is necessary to reach sustainability goals and feed a growing population through efficiency and innovation. The shift to cloud technologies benefits companies, farmers, and consumers. 

Cutting Time to Market: Leveraging Next-Generation Field Trial Software

In the field of medicine, clinical trials test the safety and effectiveness of drugs and treatments on patients. These trials must be carefully designed and executed to ensure data is collected accurately and results can be analyzed to assess safety and effectiveness. This data is also used to determine whether to continue to develop a medical solution or decide if it’s ready for launch.

Field trials in agriculture fill a similar need. For companies, universities, and even governments trying to improve sustainability, field trials are critical. They test the efficacy of agriculture products and practices on crops and soil in real-world conditions to support similar decision-making and influence farmer adoption of sustainable practices.

The trials involve testing new products, technologies, and practices that aim to improve crop yields, reduce costs, and promote sustainable agriculture. There are various steps involved in conducting a field trial, including planning, design, implementation, data collection, and statistical analysis.

Documentation and statistical analysis are critical for agricultural field trials because documentation provides a record of the trial design, methodology, and results, which allows for transparency and reproducibility of the experiment.

Statistical analysis, on the other hand, helps to identify any significant differences between treatments and provides a measure of variability within the data. This enables researchers to determine whether the observed differences are due to chance or the treatment being tested.

Without proper documentation and statistical analysis, the results of the trial may be inaccurate or unreliable, leading to incorrect conclusions and potentially costly mistakes in agricultural management practices. New-generation agriculture experiment data-gathering tools make documentation and statistical analysis easier.

The rapid development of advanced agricultural field trial tools has also made it faster for companies to transition from field trial to market. With advanced software and hardware tools, businesses can now test and validate their products in a more efficient manner, reducing the time and costs associated with traditional trial-and-error methods.

The Challenges of Traditional Field Trials

While field trials have long been an important part of agricultural research, they can also present several challenges or barriers that hinder the progress of agricultural research and development.

The high cost of field trials can be a significant barrier to conducting research in agriculture. Field trials make up an average of 35% of the crop protection industry product development process cost. Additionally, the costs of conducting field trials can vary depending on the complexity of the experiment, the number of variables involved, and the length of the trial. Accelerating time to market while managing cost constraints is critical.

The time-consuming nature of traditional field trials is another challenge faced by researchers in agriculture. Field trials can take months or even years to complete, which can delay the development and implementation of new technologies or practices. Additionally, the time required to collect and analyze data can further prolong the research process.

The potential for human error in traditional field trials is a concern that can affect the accuracy and reliability of the results. Researchers and field workers can introduce errors during data collection, measurement, or recording, which can compromise the validity of the experiment. Additionally, weather conditions and other environmental factors can affect the outcomes of the trial, further complicating the interpretation of the results.

When conducting field trials, capturing accurate data is critical. This is the output of the effort put into trials! However, a lack of standardization in data collection methods can lead to inconsistency and errors in the data. Experimental and non-experimental variables must be managed from the design stage through the trial, a clear objective must be defined, and it’s a best practice to follow standard operating procedures to ensure appropriate data is captured.

While there can be challenges related to traditional field trials, the good news is that technology can improve the execution of field trials and drive additional benefits. Addressing these barriers through field research software allows field trials to be more effective, more efficient, and conducted more often.

Next-Generation Technologies of Agronomic Field Trials

Addressing field trial-related challenges is key to improving agricultural research and managing sustainability for the future. Advanced field trial technologies like remote sensing, data analytics and machine learning, mobile data collection, and cloud-based software-as-a-solution options can collectively make huge leaps towards more efficient and effective trials.

Remote sensing and imaging technologies are becoming increasingly popular for agronomic field trials. These technologies allow for the collection of high-resolution data from the air or space, which can be used to map crop health, soil moisture, and other environmental variables. Remote sensing and imaging technologies can provide a more comprehensive and accurate view of the field, making it easier to identify patterns and trends that may not be apparent from ground-level observations. These technologies can also save time and resources by reducing the need for manual data collection.

Data analytics and machine learning are another set of advanced agricultural field trial tools. By analyzing large datasets collected from field trials, researchers can identify correlations and patterns that may not be apparent from small-scale observations. Machine learning algorithms can also be used to predict crop yields and optimize management practices based on historical data.

Internet of Things (IoT) sensors and devices are becoming increasingly popular in agronomic field trials. These devices can be used to collect data on various environmental variables, such as soil moisture, temperature, and nutrient levels. IoT sensors can transmit data in real time, providing instant feedback on the performance of crops and management practices. IoT devices can also be used to automate irrigation and fertilizer application, reducing labor costs and improving efficiency.

Real-time mobile data collection is another technology that is gaining traction in agronomic field trials. Mobile devices, such as smartphones and tablets, can be used as agriculture experiment data gathering tools to collect data from the field in real-time, reducing the need for manual entry and increasing accuracy. Real-time data collection can also provide instant feedback on the performance of crops and management practices, allowing for faster decision-making and more efficient crop management.

Cloud-based SaaS (Software as a Service) solutions are becoming increasingly popular for managing and analyzing data from agronomic field research. These field data software solutions provide a centralized platform for data collection, storage, and analysis, making it easier to manage large datasets and collaborate with other researchers.

Cloud-based solutions can also provide access to powerful data analytics tools, machine learning algorithms, and other advanced features that can improve the efficiency and accuracy of agronomic field trials. Cloud-based field data software solutions can be accessed from anywhere with an internet connection, providing greater flexibility and accessibility for researchers.

Emerging technologies such as artificial intelligence and machine learning are even enabling companies to gain valuable insights into farmer behavior and preferences, helping them to make more informed decisions about product development and marketing strategies. As a result, the new generation of technology is revolutionizing the way businesses approach the launch of new products, making the process faster, more streamlined, and ultimately more successful.

Advantages of Next-Generation Agronomic Field Trials

Advanced field trial technologies aren’t just promising options for the future. They’re delivering improved agronomic field trials today. Researchers are benefitting from more efficient and more accurate trials where they have greater control over variables and are minimizing costs. 

Increased efficiency and speed from field trial to market can be achieved through the use of next-generation field trial technologies such as data analytics and machine learning. These technologies enable researchers to analyze large datasets collected from field trials, identify correlations and patterns, and optimize management practices. For example, machine learning algorithms can be used to predict crop yields and optimize management practices based on historical data. 

This can help reduce the time and resources required to bring new products to market, giving researchers and farmers a competitive advantage. Additionally, data analytics and machine learning can help researchers identify the most promising candidates for further development, helping to streamline the product development process and bring new products to market more quickly.

Improved accuracy and precision are other advantages of using advanced field trial technologies such as remote sensing, imaging, and data analytics. These technologies provide a more comprehensive and accurate view of the field by collecting high-resolution data from the air or space and mapping crop health, soil moisture, and other environmental variables. By identifying patterns and trends that may not be apparent from small-scale observations, researchers can make better-informed decisions. 

Greater control over variables is possible through remote sensing and real-time mobile agriculture experiment data-gathering tools. Real-time data collection can also provide instant feedback on the performance of crops and management practices, allowing for faster decision-making and more efficient trial management. 

Reduced costs are another advantage of next-generation field trial technologies, such as cloud-based SaaS solutions. These technologies can help researchers and farmers manage their data more efficiently, reducing the need for manual data entry and allowing for more streamlined analysis. 

This can help reduce the costs associated with data management, freeing up resources for other aspects of the research process. Additionally, cloud-based SaaS solutions can provide a scalable and flexible infrastructure for data storage and analysis, reducing the need for costly on-premises hardware and software. This can help researchers and farmers access the latest technologies and analysis tools, without the need for significant upfront investments.

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Agmatix Puts New Generation Technology into Action 

Agmatix understands the importance of field trials for researchers and the future of agriculture. Driving sustainable agriculture practices is a key focus for Agmatix, and this is made possible by innovations discovered and implemented through field trial research. Agmatix is leading the way to advanced field trial technologies with solutions like Agronomic Trial Management and their ontology-based engine that helps to unlock the true value of data. 

The Agronomic Trial Management solution includes advanced, cloud-based field trial software that supports accurate, cost-effective, and efficient field trials from end to end. It offers a comprehensive planning process, incorporating experimental design methodologies with multiple treatment combinations and on-map layout placement. The system sends status updates to keep the trial on track and facilitates direct contact between researchers and field trial operators for efficient communication. This efficiency in trial planning has the potential to directly influence 50% of the entire product development process, reducing time-to-market while enhancing project management. 

The solution also allows users to acquire and standardize legacy data, enriching users’ information sources and ultimately enhancing decision-making. Agmatix’s solution provides access to valuable trial-derived data that are aggregated and harmonized, providing previously unavailable insights that help users make informed decisions for their future trials. With the solution’s comprehensive approach to agronomic field trial management, users can increase analysis productivity and speed up the time from trial planning to insights, empowering them to make data-driven decisions and accelerate new product development. These data-driven choices help to identify bottlenecks, support the implementation of improvements, and even support cross-trial analysis. 

Product development can benefit from improved quality control through Agmatix’s Trial Management solution, too. Managers can closely monitor trials, providing a level of control that ensures quality standards are met and performance is consistent. Users can adjust protocols and forms as well as assign tasks to field operators in real time. Managers can quickly and easily identify any issues and address them immediately. 

With the Agmatix platform, users can experience the advantages of advanced field research software from anywhere with extended mobile capabilities that are designed to simplify data collection and on-farm experiments. The mobile app is built for the field, taking into account environmental conditions. The input fields are designed to minimize errors, ensuring that the correct information is gathered at the correct location. Both online and offline data collection is possible to accommodate all situations.

Ultimately, the Agmatix platform provides the ideal vehicle for creating a competitive advantage. It’s now possible to differentiate products in the market through a better understanding of performance and marketability. Speed to market, driven by optimized trials and quick collaboration, supports your product in being first to market. But the end-to-end solution and user-friendly functionality also support improved product quality and innovation – making it a win-win for research and development. 

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From Field Trial to Market and Then to the Future 

Like in the medical field, trials are critical for agriculture. While medicine saves lives from medical challenges, agriculture faces a similar life-impacting dilemma: feeding a growing population, reducing food scarcity, and addressing climate change. 

Next-generation agronomic field trial technology is critical for increasing the speed of life-saving and life-improving innovation. Breaking through traditional field trial barriers, such as time and cost, with advanced field trial technologies has the power to move the industry faster than ever before towards a sustainable future. 

Leveraging SaaS, IoT, remote sensing, mobile capabilities, and more will empower researchers to conduct accurate trials and quickly collaborate with others to make key decisions in the product life cycle. Agmatix is proud to be innovating to power future innovations that make a global impact. 

Accelerating Innovation: Digitally Transforming Field Trials

Field trials play a crucial role in agricultural research and development by providing a means of evaluating the efficacy of new technologies and practices under real-world conditions. In agriculture, a wide range of factors can influence crop productivity, such as soil fertility, pest and disease pressures, weather conditions, and other environmental variables. 

Therefore, crop field trials provide researchers with the opportunity to test and refine their ideas in the context of these complex and dynamic systems. By conducting field trials, researchers can gain a better understanding of the performance of new technologies and practices under various conditions, identify areas for improvement, and refine their methods to increase their effectiveness.

Field trials generally adhere to a four-step procedure. Initially, the experiment is meticulously planned, encompassing the formulation of research inquiries, determination of treatments, and establishment of a suitable design. Subsequently, the experiment is executed, and data is systematically collected. Lastly, the trial results undergo analysis, enabling informed decision-making.

At each stage, the adoption of digital transformation in agricultural field research software is fostering efficiency improvements and shortens the time required to gain valuable insights. Through technological advancements, numerous innovations are being expedited, and Agmatix is at the forefront, utilizing technology to drive significant advancements in the impact of field trials.

Experiment Design and Digital Transformation in Agriculture 

Field trial experimental design involves defining the research question, managing the treatment table, and defining the design model and field layout, such as randomized complete block design or split-plot design. During this step, researchers also identify the appropriate control treatments, which help to provide a baseline against which to compare the treatments of interest.

Traditionally, experimental design has been a lengthy, time-consuming, and detailed process. Ensuring that all variables have been considered and all potential designs have been evaluated is important, and requires a high degree of collaboration with all stakeholders.

Gaining alignment across the organization can be arduous. Then, manually creating the design can be challenging, especially without the right tools at hand. Even the most experienced researchers may make errors or struggle with layout limitations without the right tools. 

New innovations in agriculture field trial technology make trial planning and design easier and faster. Drag-and-drop tools make planning and customizing experiments seamless. Users can easily build field trials that meet their needs with just the click of a button. Cloud-based technologies enhance collaboration and enable feedback in real-time, so field trial leaders can skip managing calendars and jump straight into the feedback and approval process. 

Agmatix’s Agronomic Field Trial platform enables that type of collaboration across organizations of any size and scale because it’s cloud-based. And the Agronomic Field Trial platform is a research software that makes designing the perfect trial an easier process. Researchers can easily map out layouts from a field-level view using drag-and-drop features. There are hundreds of customizable treatment combinations available in a single user-friendly interface. These time-saving features get researchers in the field faster, with fewer errors.

Conducting Experiments with Field Research Software 

The second step of a field trial is to conduct the experiment while collecting data. This involves implementing the experimental design, ensuring that the treatments are applied correctly, and collecting data on relevant variables such as crop yields, quality, pest and disease pressures, and environmental conditions. During this step, it is crucial to maintain accurate and detailed records of the experimental procedures, as well as any factors that may have influenced the results.

Traditionally, data collection in agriculture has heavily relied on manual processes. Despite the integration of certain technologies in the field, effectively combining manual data, such as pest pressure, with other data sources has posed challenges. Maintaining accurate and comprehensive records is crucial for ensuring the trial’s validity and integrity, yet the task of recording all relevant data and preserving these records is undeniably substantial. 

Digital transformation in agriculture has the immense capability of improving this data-intensive step. With Agmatix’s Agronomic Field Trial platform, data collection is a snap. Agmatix’s cloud-based next-generation tools enable extended mobile capabilities, empowering researchers and trial administrators to effortlessly collect data, whether online or offline.With full and real-time visibility of the trial, researchers can view results instantly and monitor any outliers to correct issues as they arise. 

Agronomic Trial Management also enables the organization to work under similar protocols and reduce data loss due to data standardization. The trials can be boots-on-the-ground managed by multiple individuals and still have seamless data collection. New innovations in agriculture technology are transforming field trials to make them easy and fast to execute.

Analyze Data to Drive New Innovations in Agriculture Through Technology

The third and final step of a field trial is to analyze the results to make decisions. This involves statistical analysis of the data collected during the experiment to determine the significance of the treatment effects, as well as any interactions between treatments and other factors. 

Researchers then use this information to draw conclusions about the effectiveness of the treatments tested, identify areas for improvement, and make decisions about further research or potential adoption of the treatments by farmers or other stakeholders. This step is critical for ensuring that the results of the field trial are interpreted correctly and that evidence-based decisions are made based on the data collected.

The advent of digital technology has brought about a revolutionary transformation in the analysis of agronomic field trial data. Thanks to high-speed computing and advanced software tools, the process of collecting, analyzing, and visualizing data can now be accomplished swiftly and efficiently.

Data can be analyzed using machine learning algorithms, allowing researchers to identify patterns and predict outcomes. Additionally, digital platforms can be used to share data and collaborate with other researchers and stakeholders, facilitating the dissemination of knowledge and innovation in the field.

Agmatix’s Agronomic Field Trial platform is equipped with many technical innovations to enhance field trial data analysis, making it efficient and easy. Agmatix’s platform is built on Axiom technology that ingests, standardizes, and harmonizes data from current field trials and legacy datasets to unlock the true value of the data. Agmatix’s technology often presents a comprehensive overview, offering a complete picture that was previously unavailable in many instances.

Agronomic Trial Management provides a visual interface for trial operation results and makes sharing across teams completely seamless. This cloud-based, next-generation solution makes data easily accessible for analysis by cross-functional staff members and partners – even if they’re outside your organization. 

Agmatix technology also takes data analysis one step further with technical innovations in its Insights and Models platform. Pre-built widgets help researchers to understand the data – quickly. With just a few clicks, statistical tools can improve data quality and users can create customized reports to visualize and summarize the data. These powerful tools allow researchers to conduct cross-trial analysis and dig deeper into the results of advanced farming practices. Researchers can even calibrate and verify ML models to determine the best opportunities to increase yields and sustainability. 

Ultimately, collaboration and statistical analysis are key steps in data analysis following the conclusion of in-field trial execution. Collaboration can be time-consuming, especially if data standardization and sharing are complex. The time spent completing analysis and collaborating on the next steps is valuable time researchers could be spending on continued innovation. Speed to market is critical for researchers and the industry – and digital transformation will help speed up your time to trial insights. 

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Technical Innovations in Technology Lead the Way

Digital technology has had a significant impact on the efficiency and effectiveness of field trials. The use of digital tools such as sensors, drones, and mobile applications for data collection has greatly reduced the time and effort required to collect data. This has allowed researchers to conduct more trials in a shorter amount of time, thereby increasing the amount of data collected and improving the statistical power of the experiments. 

Digital tools also enable real-time monitoring of crop growth and health, enabling researchers to respond quickly to changing conditions and adjust management strategies accordingly. Furthermore, digital data analysis tools such as machine learning algorithms can analyze large datasets quickly and accurately, leading to better decision-making and more precise results. 

Overall, the use of digital technology has improved the efficiency and effectiveness of field trials, enabling researchers to conduct more trials, collect more data, and make better-informed decisions about agricultural practices.

Agmatix supports the effort to speed time to market and drive efficiency gains in field trials. Companies can be more competitive and faster to innovate by optimizing trials and cutting time spent preparing and managing data. 

With the Agmatix suite of tools, including Agronomic Trial Management and Insights and Models, researchers can forget their Excel sheets and handwritten notes, and move into a world where data collection and analysis is effortless and efficient.

Trial and Error: Navigating Agricultural Trials with Biologicals 

Field trials play a crucial role for both farmers and research companies in the realm of agriculture. These trials are essential for evaluating the effectiveness and safety of new agricultural products, such as pesticides and genetically modified crops. For research companies, field trials provide valuable data and insights that help in the development and registration of new products.

By managing field trials, researchers can assess the effectiveness and environmental impact of their products, determine their efficacy in real-world conditions, and identify any potential risks associated with their use. This information is vital for ensuring the sustainability and responsible deployment of agricultural technologies.

Field trials help farmers make informed decisions about new agricultural practices and products. By participating in or accessing results, farmers can optimize production, increase yields, reduce environmental impact, and improve economic viability.

Field trials serve as a bridge between research companies and farmers, offering vital information for the development of new agricultural products and aiding farmers in making informed decisions. These trials ensure the responsible use of technologies, promote sustainable farming practices and contribute to the overall advancement of agriculture. 

When it comes to field trials for biologicals specifically, research companies and growers both can see significant benefits from deeply understanding product efficacy and innovations moving faster to market. 

Ag Biologicals and Field Trials

Typical agricultural field trials include key steps such as planning, trial management, and data collection and analysis. 

The first step in conducting field trials is careful planning. This involves defining the objectives of the trial, selecting appropriate trial sites that represent the target conditions, identifying the specific treatments or inputs to be tested, and determining the agronomic field trial design strategy. Factors such as sample size, randomization, and replication are considered during the planning phase to ensure statistical rigor.

Once the trial is planned, management includes activities such as preparing the trial site, implementing the treatments according to the experimental design, and maintaining appropriate control plots. Trial management also involves monitoring and managing factors that can influence the trial outcomes, such as irrigation, pest control, and weather conditions. Regular observations and documentation of any deviations from the planned protocols are important for maintaining the integrity of the trial.

Accurate and systematic data collection is a critical step in agricultural field trials. It involves gathering relevant information on various parameters, such as crop growth, yield, pest incidence, and environmental conditions. Data collection methods may include measurements, observations, surveys, or sample collection. Once the data is collected, it needs to be organized, validated and analyzed using appropriate statistical techniques. Data analysis helps in determining the significance of treatment effects, identifying patterns or trends, and drawing conclusions or making recommendations based on the trial results.

Biocontrol Trials 

Testing biological controls in a field setting is a critical step in a company’s journey to bring new innovations to market. Synthetic molecules alone can be very challenging to innovate with – but including ag biologicals in the product, roadmap can reduce the cost of bringing a plant protection product to market. The right practices for demonstrating efficacy and showing value for both farmers but also potential investors are critical for moving their products forward. 

These naturally occurring bio-pesticide, bio-stimulants, and bio-fertilizers are often applied alongside a synthetic fertilizer to make nutrients more available to the plant. Biostimulants and biofertilizers that support nitrogen fixing and nitrogen availability. 

The agriculture biologicals market is becoming increasingly competitive. It’s expected to grow at a CAGR of 13.7% between 2023 and 2028. Eventually, the market will reach an estimated value of 27.9 USD, driven by consumer focus on environmental safety and an ideal regulatory environment. 

Key players in the plant protection and agriculture biologicals market are leveraging new product launches, expansions, and agreements to drive the business forward at a rapid pace. Differentiation continues to be critical for success in the ag biologicals space. 

However, there is a natural skepticism around biologicals and their efficacy. A recent university study underscored this skepticism after working through 60 years of data and concluding that farmers should be diligent in researching the claims companies make regarding the performance of biostimulants. 

Farmers may be concerned specifically with increasing yields or the protection of plant yield while reducing synthetic fertilizer application rates. All of these factors will help them determine a return on the investment in ag biologicals as part of their strategy to manage their crops. 

Farmer sentiment in regard to biostimulants as a tool to manage crops varies. Around 39% of farmers have a positive attitude about biologicals, but nearly the same amount – nearly 31% – have negative feelings towards biostimulants. Only 23% of those used a biostimulant in 2022 – so there is ground to gain in market growth and farmer opinion of the products. This further underscores the importance of field trials in demonstrating localized product efficacy. 

Another opportunity in the ag biostimulant market is the increasing merger and acquisition activity. Well-established crop protection and nutrient companies are investing in biopesticide companies to enter the market in a substantial way. These deals are aligned with increased research and development dollars and subsequent product launches that are expected to match growing demand and eventually lead to increased prices. 

Agmatix and Field Trials for Biologicals 

Agmatix is an agro-informatics technology company focused on helping farmers farm more sustainably through data-informed decision-making. Agmatix’s industry-exclusive approach to data harmonization is the backbone of the Agronomic Trial Management platform. 

The Agronomic Trial Management platform is an important tool in biocontrol trials. Testing biological controls requires an effective trial strategy, management, and data management. By following the key steps of agronomic trials noted above and using an ag technology platform to manage the trial efficiently and effectively, companies can increase their speed to market and demonstrate product efficacy to a skeptical audience. This is a key competitive advantage. 

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Agronomic Trial Management 

This ag technology platform is designed specifically to increase the efficiency of agronomic trials and enhance the quality of field trial data. It’s an end-to-end solution that allows field trial coordinators and research scientists to cover all steps of a field trial in one place – from planning to operating and eventually managing and analyzing trial data. 

The user-friendly platform enhances collaboration while also providing full control of the trial’s status. The system provides trial layout options and customizable treatment combinations that work hand-in-hand with flexible data collection. 

The Agronomic Trial Management platform even allows users to view data results in near real-time. This level of monitoring reduces the risk of human error and even data loss. Data integrity is ensured when field trial operators can monitor for outliers and validate the trial in the course of trial operations. 

The Biocontrols Trials Opportunity with Agronomic Trial Management

The Agronomic Trial Management product is an excellent resource for companies navigating a changing regulatory environment and looking to position themselves for purchase. 

The regulatory environment for biologicals is fluid and expected to continue to change. Agronomic Trial Management is an excellent tool for capturing and storing trial data today, and future additional features will only make navigating the regulatory environment more efficient and streamlined. 

Niche biopesticide companies can leverage the power of high-quality agronomic data to prove the value of their company and the efficacy of their products. In a competitive market filled with startups and niche products, bringing high-integrity data to the negotiation table can be a huge difference-maker. Agronomic Trial Management provides an easy and efficient way to manage trials and capture accurate data. It also allows companies to ingest other datasets and compare legacy data sources to create comprehensive and cohesive analyses to support the valuation of their businesses. 

As Ag biological companies expand globally, they don’t just have to worry about differing regulatory environments; they also have to consider the best ways to prove efficacy as they expand into different growing environments. Testing biocontrols in a way that provides localized data at scale can increase speed to market and even support product launches in multiple markets simultaneously. 

This testing is key for overcoming challenges related to farmer sentiment. Agronomic Trial Management is designed to support global field trials and large teams while enabling efficient collaboration and easy data sharing. This streamlined approach supports companies in meeting local regulatory requirements and demonstrating localized value to farmers all over the globe. 

Agronomic Trial Management is an excellent tool to support the work of companies that are navigating the ag biologicals market. In this ever-changing and competitive market, a sound foundation of high-quality data and efficient field trial management can make all the difference in positioning a product or company for success. 

Achieve Higher Yields, Cost Savings, and Reduced Carbon Footprint with Precise Agricultural Data

Farming is a challenging business. Managing uncontrollable variables like weather and markets, addressing changing pest and disease pressure, and running a complex business can make farming difficult. Add in the impacts of a changing climate and the pressure to feed a growing world, and at times, the challenges can feel insurmountable. 

It’s no wonder that farmers are turning to precise tools to help them grow their yields, lower input costs, and farm in a sustainable way. In fact, the precision ag industry is expected to grow at a CAGR of 12.6% between 2023 and 2030. Precise agricultural data fuels key tools to increase yields, spend less, and lower carbon footprint at the farm level. 

Increasing Yields with Precise Agricultural Data

Precision agriculture enables farmers to make informed decisions about crop management by gathering and analyzing data related to soil moisture, nutrient levels, and crop growth. By using this data to make adjustments to their management practices, farmers can optimize yields and increase their profitability. These benefits are driving precision agriculture data usage

Precision agriculture technologies like sensors and drones can provide farmers with real-time data about their fields. This data can be used to monitor crop growth, detect early signs of pest or disease pressure, and adjust irrigation and fertilizer applications as needed.

Precision agriculture tools like Digital Crop Advisor allow farmers to collaborate with agronomists to optimize their crop management practices. This software provides real-time data and recommendations based on factors like soil and weather conditions, helping farmers make informed decisions about their crop management strategies. By working with agronomists and utilizing these tools, farmers can further optimize their yields and reduce their environmental impact.

Spending Less with Precise Agricultural Data

Precision agriculture can help farmers reduce expenses by only applying inputs exactly where they are needed and reducing overlap. Precise data can be used to optimize the use of resources, such as fertilizers, which have improved placement efficiency by an estimated 7% with the potential to further improve an additional 14%. 

Precise data from on-farm experiments can help farmers minimize risk and dollars spent on unproven products and production practices. Overall, in several studies, precision agriculture technologies have proven savings through variable rate planting, precise nitrogen application, and enhanced pest management. 

Reducing Carbon Footprint in Agriculture with Precise Agricultural Data

How much CO2 is produced from agriculture? 

Carbon footprint in agriculture is a significant contributor to global greenhouse gas (GHG) emissions, with estimates suggesting that agriculture contributes 10-12% of global GHG emissions. According to the United Nations Food and Agriculture Organization (FAO), the world’s livestock industry alone produces more greenhouse gases than all the cars, trucks, planes, and ships in the world combined. Therefore, it’s essential to lower the carbon footprint in agriculture to mitigate climate change.

How is carbon footprint calculated in agriculture? 

To calculate the carbon footprint in agriculture, different methods can be used, for example as part of a life cycle assessment (LCA) approach. LCA is a comprehensive method that considers all GHG emissions produced throughout the entire agricultural production cycle, including fertilizer production, land-use change, transportation, and the use of inputs such as pesticides and herbicides. By using this approach, various stakeholders, including researchers and farmers,  can identify the primary sources of GHG emissions in a farming system, and take necessary steps to reduce them.

Precision agriculture can play a significant role in reducing the carbon footprint in agriculture. By using precise data and technology, farmers can optimize their input use, reduce waste, and improve crop yields while minimizing GHG emissions. Precision agriculture helps farmers adopt more sustainable practices, such as reducing tillage, optimizing fertilizer and pesticide application, and improving irrigation efficiency. 

For instance, precise data has enabled farmers to reduce herbicide use by an estimated 9%, with the potential to further decrease it by 15% at full adoption. Such practices can significantly reduce carbon footprint in agriculture while also improving farmers’ profitability and sustainability.

Agmatix’s Digital Crop Advisor tool includes a fertilizer carbon footprint optimizer that helps agronomists and decision-makers on the farm compare nutrition plans and understand tradeoffs between yield and environmental impact. The tool even has an understanding of fertilizer production carbon footprint and takes this into account when providing recommendations. 

By incorporating these tools and technologies, farmers can reduce their Scope 3 emissions in agriculture, including emissions from fertilizer and pesticide production, transportation, and waste disposal. Therefore, precision agriculture is a crucial tool that can help farmers reduce their carbon footprint while improving their productivity and profitability.

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Agmatix Supports Precise Data 

As a global agro-informatics company, Agmatix understands the importance of precise data for positioning farmers to produce more, earn more, and protect the environment. Agmatix’s suite of on-cloud, next generation solutions support data generation, fast utilization, and data sharing to enable collaboration and ultimately speed to market. 

The Digital Crop Advisor solution supports growers in calculating and reducing carbon footprint in agriculture through data-driven decision-making. Agronomics can leverage site-specific data to make customized nutrient recommendations designed for lowering Scope 3 emissions in agriculture. 

Through the utilization of Digital Crop Advisor, crop yields can be maximized and sustainability KPIs can be quantified. Leveraging tools like Digital Crop Advisor in agriculture supports an understanding of how much CO2 is produced from a given set of nutrition protocols. Digital Crop Advisor can also support an understanding of fertilizer production carbon footprint, and the system recommends the most sustainable options and alternatives. 

Digital Crop Advisor supports real-time decision-making in over 150 crops using 12 crop nutrient data profiles. Reporting and analysis of data are early, enabling even global teams to review and make decisions together. The decision support system enables agronomists to be confident in supplying growers with actionable, sustainable nutrition plans that work towards lowering agriculture’s carbon footprint. 

The Agmatix platform is supported by a foundation engine that enables data to reach its full potential. Axiom is an ontology-based engine that ingests data from field trials, legacy data, IoT sensors, and other sources. It validates the data, serving as a quality gate and a standardizing step. Then, the data can be enriched with other datasets and transformed or harmonized for maximum use. Using data science and AI, Axiom unlocks field-level decisions and maximum data-driven sustainability. Axiom defines precise agricultural data! 

Agmatix provides cloud-based solutions that work in diverse ways to support the use of data to increase yields, lower costs, and reduce scope 3 emissions in agriculture. These technologies are advanced, next-generation technologies that support everything from calculating and reducing carbon footprint to increasing speed to market and harmonizing data to support its use across the production system. Through precise agriculture data, a brighter future is possible. 

Cloud Computing: Reshaping the Ag Industry

Cloud computing has revolutionized the technology landscape by providing numerous benefits that drive innovation and accelerate technological advancement. One key advantage is the cost savings it offers. By leveraging cloud services, businesses and individuals can reduce upfront infrastructure costs as they no longer need to invest in expensive hardware and software. Instead, they can access computing resources on-demand and pay only for the resources they use, resulting in significant cost savings.

Scalability is another area where cloud computing excels. Traditional on-premises infrastructure often struggles to handle sudden spikes in demand, leading to performance issues or downtime. In contrast, cloud computing allows for seamless scalability, enabling businesses to quickly and easily expand or shrink their resources based on fluctuating needs. This scalability empowers organizations to respond swiftly to market demands, accommodate growth, and avoid costly infrastructure overprovisioning or underutilization.

Furthermore, cloud computing fosters innovation by democratizing access to advanced technologies. It provides a platform for developers and businesses to experiment, prototype, and deploy new ideas rapidly. Cloud-based services offer a wide range of tools, such as machine learning, artificial intelligence, and big data analytics, which were previously accessible only to large organizations with substantial resources. This democratization of technology fuels innovation across various industries, enabling businesses to leverage cutting-edge capabilities and create new products, services, and solutions.

In the tech industry, there are many examples of the power of cloud computing. Uber’s transformative impact on the taxi industry can be attributed, in large part, to its utilization of cloud computing. Unlike traditional taxi services that rely on manual dispatch processes, Uber leverages cloud-based automation to manage its rideshare operations. By operating as an interface for millions of customers worldwide, Uber effectively connects riders with drivers using automated services enabled by cloud computing.

During peak times such as Halloween or New Year’s Day, Uber experiences a substantial surge in demand for infrastructure resources. This surge, ranging from 50% to 100%, would overwhelm a conventional taxi service still reliant on manual dispatch systems. However, Uber addresses this challenge by leveraging the power of auto-scaling in cloud infrastructure. This cloud-based auto-scaling allows Uber to dynamically allocate and scale computing resources in response to demand fluctuations, ensuring seamless and efficient service delivery during high-volume periods. This creates a competitive edge and has allowed Uber to disrupt the taxi industry by creating a more convenient and reliable alternative to legacy modes of transportation. 

The agriculture industry stands to gain just as much – if not more – through cloud computing applications. The same opportunities to disrupt traditional methods through scalability and speed to marketing exist in the industry, and edge computing can be a seamless vehicle to deliver on these opportunities. 

Impact of Cloud Computing on Agriculture 

One of the major challenges in agriculture today is the need to sustainably increase food production to feed a growing global population while minimizing environmental impact and conserving natural resources. Another challenge is the impact of climate change, which brings unpredictable weather patterns, extreme temperatures, and changing pest and disease dynamics, requiring farmers to adapt their practices and adopt resilient agricultural techniques. Addressing these challenges will require new technologies and new ways of farming. 

Cloud computing brings the same benefits to the agriculture industry as it does to the tech industry: cost savings, scalability, and innovation. The industry is taking notice – companies invested 340.4 billion dollars in cloud computing in 2021. 

An increasing number of agriculture companies are recognizing the tangible advantages of cloud computing, which has long been regarded as a driving force for innovation and digital transformation. Its capacity to accelerate development processes and offer virtually unlimited scalability is proving to be a significant factor in enhancing operational speed and efficiency for businesses.

Cloud Computing for Innovation and Research 

The agriculture industry is already immersed in data derived from trials and real-world scenarios. Adopting a data-as-a-product operating model streamlines data accessibility for development teams, significantly reducing the time required to execute use cases by three to six months

This approach ensures that data is readily discoverable and available, empowering development teams to leverage it more efficiently in their projects. The cloud plays a pivotal role in enabling and expediting this transformation. 

Organizations can tap into new business opportunities by expanding the accessibility of data for analytics use cases. Data can be securely shared among ecosystems and corporate alliances, fostering data availability and facilitating the consolidation of data architecture across diverse business units through promoting standardization and supporting a singular governance model for maximum efficiency. 

Cloud computing applications in agriculture can make a real impact on business operations. Expediting the development and deployment of cutting-edge analytics has the potential to drive revenue growth by up to 20 percent. Furthermore, integrated cloud services enable organizations to stay ahead of technological trends and advancements through faster innovation cycles, ensuring they remain at the forefront of industry developments. 

By automating infrastructure orchestration and monitoring, as well as dynamically adjusting provisioned compute resources based on workload requirements, organizations can achieve significant cost savings of up to 20 percent in their infrastructure expenses.

These edge computing-driven innovations are already making waves in agriculture. In India, agtech innovation driven by digital marketplaces and farmer financing through digital solutions could grow Indian farmer income upwards of 25%. Cloud computing is supporting innovations that enable faster data sharing between farmers and agronomists or within commercial companies producing ag inputs. 

And perhaps most important of all, cloud computing can support digital transformation in the industry that leads food and agriculture to net zero emissions. Next-generation technologies can enable that transition, which will change how food is produced and what food we eat. 

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The cloud-based ag data train is about to leave the station – are you on it?

Agmatix Enables Cloud Computing in Agriculture 

Agmatix, the cutting-edge agro-informatics platform, is built entirely on powerful cloud infrastructure. Because of these cloud capabilities, Agmatix delivers a robust Software-as-a-Service (SaaS) solution. 

With its proprietary machine learning algorithms, Agmatix analyzes numerous agricultural industry data points to assist scientists, agronomists, and farmers in making informed decisions, leading to improved crop yields and quality. 

Agmatix combines extensive research, real-world data, and valuable industry insights within an advanced system, showcasing immense potential. This marks just the initial phase of the emerging AgTech landscape, which presents a fertile ground for growing data for impact. 

Agmatix technology pioneers as the world’s first engine to seamlessly bridge the agronomic innovation cycle, translating research and experimental data into actionable real-life solutions. By creating a unique data language, Agmatix has the ability to read and interpret a wide range of data points commonly employed within the agricultural industry. This innovation is powered by edge computing and has the potential to make the key difference in a company’s efficiency and impact in the agriculture space. 

The high quality and standardized agronomic data provided by Agmatix through cloud computing presents many opportunities for agriculture companies to create efficient operations and be faster to market. In each deployment of a cloud-based product, companies have the potential to disrupt the industry and make a meaningful impact on the future of sustainable agriculture. 

Ron Baruchi, CEO of Agmatix, explains, “Growers, agronomists, researchers, and ag industry experts are tackling today’s biggest challenge – providing food security for the world’s growing population. While searching for a solution, each of them is creating and collecting vast amounts of data and expertise. 

But In order to face this epic challenge, they will need to be able to share the data and knowledge between them. Our technology provides a solution that unites, standardizes, and leverages agricultural data, allowing it to effectively manage agronomic research trials and translate them into real-life practices in a one-stop-shop.” 

These capabilities empower agriculture and technology professionals worldwide. Explore how these new generation cloud-based solutions are optimizing how real-world companies innovate and operate. 

Turning Agronomic Data into Actionable Insights: An Overview of Axiom Technology

Agmatix is a global agro-informatics company focused on delivering actionable insights to the agriculture industry. Agmatix’s vision is a world where standardized agronomic data of maximum quality is available to support agriculture professionals to overcome sustainable food production challenges. 

Through the development of data-driven solutions in a cutting-edge platform based on agronomy data science and advanced AI, Agmatix aims to address the lack of data standardization in agriculture to maximize crop yield while supporting sustainable agriculture. 

Axiom technology is the backbone of Agmatix’s agronomist and research-focused platforms. Axiom is an ontology-based engine that enables data to reach maximum value through ingestion, validation, enrichment, and harmonization. 

When data is in its highest quality and most usable state, it can be used for modeling, predictive insights, or data-driven decision-making through the Agmatix platforms. Ultimately, this comprehensive connection between Axiom and the end use of the data means decisions can be made in a more efficient, informed manner. 

What is Agmatix’s Axiom Technology?

To make sense of the vast amount of data generated by field trials and other agricultural pursuits, Agmatix developed the Axiom technology. This technology takes in and organizes data from various sources, such as APIs, remote sensors, and data repositories. By using in-house ontologies, Axiom is able to standardize and harmonize this data, making it more useful for predictive modeling, research, and field trials in agriculture. 

Axiom’s technology uses its own data protocol called Growing Universal Agronomic Data Standards (GUARDS). GUARDS is designed to transform the diverse methods that researchers use to store raw agronomic data into a universal standardized language that can be easily comprehended by any researcher globally. 

GUARDS organizes all of the parameters in the agriculture space – including nutrients, crops, soil characteristics, and more – into a knowledge graph with many connections inside the graph. It adheres to the FAIR data principles, which guarantee that data is Findable, Accessible, Interpretable, and Reusable. This GUARDS protocol is the key ontology, and it’s expanding. 

Axiom also automatically takes in agronomic data from multiple sources, ensuring the highest levels of integrity. By using agronomic big data and the latest technology, Axiom makes it possible to create agronomic predictive models, ontology repositories, and statistical analyses for agriculture. 

We then employ our advanced analytics software to process the standardized and analyzed data, generating machine learning-based predictive models for agricultural solutions, analytics, APIs, and data service digital solutions. 

By using Agmatix, agriculture professionals can finally focus on generating insights rather than spending 80% of their time acquiring clean agricultural data. This approach significantly reduces the time it takes to bring new innovations to market in the industry.

How Axiom Works 

Axiom works through a process to ensure agronomic data is in its most usable format. That starts with data ingestion, where data comes into the platform from current and past research. Data can also come from APIs and IoT sensors – or even an agronomic database

After ingestion, the data undergoes a series of pipelines to achieve quality, enrichment, and standardization. Here are three examples of our main pipelines:

  1. The first pipeline is the quality gate, which utilizes machine learning to identify anomalies. It thoroughly cleanses the data, ensuring data integrity from multiple sources such as date, location, and incorrect values, among others, before any further manipulation.
  1. Once the data is clean, it proceeds to the enrichment gate. This layer enhances the data by generating additional knowledge without altering the original data, ensuring its safety and security. Within the data enrichment gate, there are several pipelines, one of which addresses the normalization problem concerning units. This pipeline, known as the unit converter, consolidates diverse measurements into a standardized baseline.
  1. The final gate is the standardization gate, which establishes the data model for standardization before storing the information in the data warehouse. The standardization and data modeling processes adhere to the GUARDS protocol.

The bottom-up ontology engine uses a bottom-up approach to create standard definitions based on the data. 

Overall, the GUARDS protocol orders data into a knowledge graph with many connections inside the graph, which allows a user to find the answer to any question – without data barriers prohibiting searching for the answer. 

Once the data has been standardized through the GUARDS protocol, Axiom generates insights and models to support analytics and field-level applications of the data through ML. The interaction layer enables modeling through the implementation of the knowledge graph to promote agricultural predictions. 

We are building a unique modular data lake infrastructure which serves agronomists to control, provision, and retrieve any information from each pipeline while assuring that all original data is safe and secure as required by our customers, said Dan Raudnitz, Vice President of Research and Development at Agmatix

What Makes Axiom Technology Powerful

Axiom technology supports resilient agriculture by enabling dynamic decision-making through agronomic data management and insights. Axiom unlocks the true potential of agronomic data for businesses, leading to an increased return on investment in research and development. 

Axiom lays the groundwork for digital transformation in research and development companies, allowing data to be a catalyst for increased speed to market. To enhance decision-making and increase the velocity of results, Axiom breaks down data silos and provides access to data throughout an organization and its partners. Ultimately, this promotes information sharing among divisions, functions, and even with growers.

For researchers and data scientists, the effortless stitching together of data and systems through Axiom leads to expedited innovation and the development of new products through accessing readily available ML-ready data pipelines.

Axiom is an industry-exclusive technology that promotes scientific agriculture predictions through the implementation of knowledge graphs. 

For Agmatix, this is at the heart of everything we do – our North Star. Using the GUARDS protocol, it’s possible to pull data from different places and standardize it, regardless of source. This data can be enriched with adjacent data layers to provide a more complete dataset for analysis. Axiom even provides a download API view and self-analysis capabilities to make the most of the agronomic data. 

Applications of Agmatix Axiom Technology: How Agmatix can help Ag Professionals with Agronomic Data Insights

Axiom serves as the central backbone for the Agmatix platform that enable agriculture professionals to collect and share agronomic data and to discover unique insights that are actionable at the field level, supporting sustainability, crop quality, and yield goals. 

Agronomic Trial Management is an end-to-end research trial management platform that ultimately increases speed to market. This one central solution includes trial planning and layout options, allows users to manage trial execution, supports data collection, and even includes analytic widgets for fast data analysis. Data and reports can easily be shared with cross-functional teams to speed up decision-making across stakeholders. 

Digital Crop Advisor supports agriculture professionals in helping farmers to maximize profits and simultaneously reduce environmental impact. This decision support system is based on scientific principles and backed by data to assist in optimizing crop nutrient plans. A mobile application even works with the unified global platform for in-field data collection to support agile nutrition plans. 

Because of Axiom technology, Digital Crop Advisor can provide unique insights into sustainability KPIs, including carbon footprint. Users can even simulate tradeoffs between different nutritional plans and their potential impacts on yield and carbon footprint. This information enables field-level decision-making with the environment in mind. 

Insights and Models provide agronomic analysis powered by Axiom. Insights and Models enable a comprehensive view of agronomic trial outcomes. By analyzing combined and standardized field trial data, it creates dynamic crop models and provides deeper insights into the results.

Key Features of Agmatix’s Axiom Technology

Axiom technology is a unique approach to data standardization. This platform deploys a graph data structure that enables AI and modeling capabilities to make the most of the dataset. Powerful analytics cluster data based on ontology hierarchies, exposing relationships between different entities – even if they are from different domains. 

Combined with relevant layers, such as weather or GIS data, Axiom’s auto-standardization of fragmented data based on the GUARDS protocol allows Axiom to go where other tools can’t – directly to fully unlock the potential for the data. 

For field trials, the automatic process to fuse data from current and ongoing trials with legacy trials into a single, standardized data lake allows companies to see the full picture of a product and its potential. Axiom both enriches and acquires data. The addition of relevant data helps round out the dataset and provide complete analytic results. 

“In the enrichment layer, we are doing some kind of calculation on the data, on the raw data. For example, efficacy, there’s no parameter that is important for us in order to make further analysis going forward. So we do some enrichment on the raw data on some of it and add this enrichment layer to our data lake as well,” said Dan Raudnitz, Vice President of Research and Development at Agmatix. 

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Axiom Enables Agronomic Data Insights

Axiom technology provides the methodology to fuel digital transformation in agriculture. Axiom helps break down data silos through ingestion and standardization in accordance with the FAIR data principles. 

This enables data-driven decision-making in agriculture, supporting increased innovation to address the need for increasing production, quality, and sustainability. As Mr. Raudnitz says, “Agmatix is where we can change the world.” 

Agmatix and NASA Harvest Join Forces to Promote Sustainable Agriculture

Sustainable agriculture will play a critical role in food security, natural resource preservation, and community quality of life, it focuses on producing food in a way that is environmentally, socially, and economically sustainable. Sustainable farming practices help to protect and conserve natural resources that agriculture depends on, such as soil, water, and biodiversity. 

Food security can be attained by producing enough food to meet the demands of a growing population despite environmental stresses. And sustainable agriculture can improve the economic viability of farming by reducing input costs, increasing yields, and enhancing market access. 

Sustainable agriculture has been a key topic in agriculture and natural resource conservation for some time now. But that doesn’t mean the need for sustainable practices in agriculture is decreasing. In fact, climate-resilient sustainable agriculture is becoming more critical as impacts of climate change, such as changes in weather patterns and extreme weather events, become more evident. 

Farmers must produce food in a climate-resilient way while also increasing productivity to address the needs of a growing population. Sustainable agricultural practices can help meet these goals by using techniques that promote long-term environmental stability and economic viability. 

By using sustainable agriculture methods, farmers can improve soil health, minimize the use of chemicals and other inputs, and increase crop yields. In this way, sustainable agriculture plays a critical role in meeting the increasing demand for food, creating climate resilience, and ensuring the health of the planet for future generations. 

Sustainable agriculture’s role in creating resilience in agriculture is undoubted. But, it takes innovation to support new sustainable farming practices and support the adoption of these practices at the farm level. This is why Agmatix and NASA Harvest have joined forces, leveraging cutting-edge next-generation technologies to propel sustainable agriculture to new heights. 

The Agmatix and NASA Harvest Partnership

NASA Harvest and Agmatix have recently formed a partnership to support sustainable crop production and mitigate the impacts of climate change. The main goal of this partnership is to promote resilient agriculture worldwide by utilizing NASA’s remote sensing technologies and Agmatix’s digital platform to provide farmers with data-driven insights that can inform sustainable agricultural practices.

NASA Harvest is a program that uses satellite imagery and data to monitor and forecast agricultural productivity and food security around the world. By partnering with Agmatix, a leading provider of digital agriculture solutions and precision agriculture tools, NASA Harvest aims to deliver actionable information to different agricultural stakeholders to promote sustainable ag production.

“NASA Harvest is excited to partner with Agmatix to advance the use of satellite-based information to help inform on-farm decisions which can ultimately result in increased resilience while reducing waste,” said Inbal Becker-Reshef, Director of NASA Harvest.

Agmatix’s digital platform allows farmers to collect and analyze data on their crops and soil conditions, providing them with insights on how to optimize their farming practices for sustainable and resilient agriculture. 

By integrating NASA’s remote sensing data with Agmatix’s smart agriculture platform, farmers can gain a more comprehensive understanding of their fields and make informed decisions that can improve productivity, reduce costs, and mitigate the impact of climate change on their operations. It’s an excellent combination for creating resilience. 

A Partnership for Sustainability

The partnership between NASA Harvest and Agmatix aims to support sustainable crop production at the field level by empowering farmers with the tools and knowledge needed to make informed decisions about their farming practices. 

This will help to promote the uptake of sustainable agricultural practices and mitigate the impact of climate change on agriculture worldwide. By harnessing the power of remote sensing and digital agriculture, this partnership has the potential to transform the way farmers manage their crops and address the pressing challenges facing global food security.

Collaborations between technology companies and research institutions, like that between Agmatix and NASA Harvest, are critical for promoting sustainable agriculture. By sharing and integrating data from various sources, including open-source agricultural data, farmers and agricultural stakeholders can gain a more comprehensive understanding of their fields and make informed decisions about their farming practices. 

Technology companies and research institutions can work together to develop tools and platforms that enable farmers to collect, analyze, and utilize data to optimize their operations, reduce costs, and mitigate the impact of climate change on agriculture. By fostering collaboration and innovation, partnerships can help to accelerate the adoption of sustainable agricultural practices and promote the long-term health of the planet.

The Role of Technology in Sustainable Agriculture

Technology is an integral part of sustainable agriculture. In fact, some would say it’s the basis for it. Technology has the capability to increase the stability and productivity of agriculture. There are a variety of tools and technologies that are being developed and implemented to support sustainable agriculture, including precision agriculture, drones, soil sensors, and renewable energy.

Precision agriculture involves the use of data-driven decision-making tools to optimize the use of inputs such as water, fertilizer, and pesticides. By using precision agriculture, farmers can reduce waste, increase efficiency, and promote sustainability. 

Drones are also being used in agriculture to collect data on crop health and yield, which can inform targeted interventions and improve decision-making. Soil sensors provide real-time data on soil moisture and nutrient levels, allowing farmers to optimize irrigation, reduce fertilizer carbon footprint, reduce costs, and promote sustainability.

Farmers can achieve productivity, precision, and prediction in their operations by combining the right technology and processes. For example, farmers can apply optimized amounts of fertilizer in real-time, in exactly the right place, monitor conditions with greater accuracy, and leverage data to drive continuous improvements. Incremental year-over-year gains can accumulate to make significant strides towards sustainable agriculture at scale.

The Sky’s the Limit with Agmatix and Sustainability

Agmatix’s platform leverages data to support sustainable agriculture through data-driven decisions. The Digital Crop Advisor platform generates customized fertilization plans for up to 12 nutrients at the field level. The plans are tailored to site-specific needs such as crop type, geography, seasonality, and production goals. This enables agronomists to support farmers in growing yields sustainably and getting the best value out of every crop. 

Digital Crop Advisor is also equipped with specific tools to support sustainability. With deep insight into yields, quality, and carbon emissions, it’s possible to optimize operations to be productive and environmentally friendly. 

The platform offers sustainable nutrient recommendations for each individual plan created, taking into account a unique carbon footprint analysis. This enables users to measure and compare key sustainability indicators such as carbon footprint and nitrogen leaching. Users can even analyze trade-offs between maximizing yields and minimizing the environmental impacts of a nutrient plan. 

The Importance of Resilience in Agriculture

Resilient agriculture is a concept that emphasizes the need to build agricultural systems that can withstand and adapt to environmental stresses and shocks, such as climate change, drought, floods, and soil degradation. 

By definition, it is an approach that recognizes the interdependence between agriculture, the environment, and human well-being and aims to create systems that are both productive and sustainable in the long term. Resilient agriculture is what is critical for ensuring food security and livelihoods, particularly in vulnerable regions that are highly dependent on agriculture for their survival.

Resilient agriculture will have an even more important meaning for the industry as growers start to see more of the impacts of climate change. Unpredictable weather patterns and extreme weather events all have the potential to upset agricultural practices that have been used for generations and destroy entire crops. Implementing agricultural production practices that fit the definition of resilient agriculture will help farmers sustain their livelihoods and future-proof food production. 

Resilient Agriculture In Practice 

Around the world, projects and efforts are popping up to define the meaning of resilient agriculture at the ground level. What resilient agriculture is might differ for a country, region, or farm. For North Macedonia, a special project will focus on climate change adaptation and mitigation, plus GHG-minimizing activities in the agricultural industry.  On the other hand, the Maharashtra Project for Climate Resilient Agriculture targets smart agriculture practices related to improved irrigation and drainage for creating resilience. 

Sustainable practices play a key role in climate-resilient agriculture. Ultimately, many of these practices help farmers adapt to changing conditions and cope with climate-related challenges. One of the key ways in which sustainable agricultural practices can contribute to resilient agriculture is by promoting soil health. 

Soil is a critical component of agricultural productivity, and sustainable farming practices can help to maintain and improve soil structure and fertility, reduce erosion, and increase water retention. This, in turn, can help to reduce the impact of droughts and other weather events on crop yields.

Another way in which sustainable agriculture practices can contribute to resilient agriculture is by promoting biodiversity. By using techniques like crop rotation, intercropping, and the use of cover crops, farmers can promote the diversity of plant and animal species on their land. This can help to reduce the impact of pests and diseases on crops, as well as provide a buffer against weather events.

In addition, sustainable agricultural practices can help to reduce greenhouse gas emissions, which are a major contributor to climate change. Techniques like conservation tillage, which involves reducing or eliminating tillage, can help to sequester carbon in the soil. Optimized nutrition planning can help lower the carbon footprint of crop fertilization. 

The potential benefits of resilient agriculture for food security and sustainable development are significant. By increasing the ability of farmers to adapt to changing environmental conditions, resilient agriculture can help to ensure that food production remains stable and reliable, even in the face of natural disasters, climate change, and other challenges. This, in turn, can help to ensure that people have access to the food they need to live healthy and productive lives.

Resilient agriculture can also play an important role in sustainable development, by promoting economic growth and social well-being. By increasing agricultural productivity, food security is improved and economic development can be increased. Particularly in areas that are vulnerable to weather-related disasters and economic instability, resilient agriculture can help reduce vulnerability and protect communities. 

Ultimately, the potential impact of smart agriculture for creating resilience is what led to the Agmatix and NASA Harvest partnership. 

“According to the World Economic Forum, sustainable agriculture practices must triple in order to prevent climate change. Currently, adoption is hindered by a lack of consistent and acceptable measurements at scale. Our collaboration will promote resilient agriculture beginning with smallholder farms in India and commercial farms in Brazil, and lead to further expansion worldwide,” comments Ron Baruchi, CEO of Agmatix.

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Agmatix and NASA Harvest for Resilience in Agriculture

The partnership between Agmatix and NASA Harvest is just the start of impactful work that will bring new meaning to resilient agriculture. This project will enable big gains in sustainable agriculture and help create climate resiliency at a time when these practices matter more than ever. This partnership is a big leap forward to supporting sustainable agriculture at scale and around the world. 

Boosting Agricultural Output: The Impact of Digital Transformation and Data Analysis in Field Trials

Digital transformation in agriculture is increasing sustainability and providing unlimited opportunity. According to McKinsey, agriculture’s connected future will spur new growth, while the Food and Agriculture Organization (FAO) is promoting digital agriculture as a means to achieve sustainable agriculture and improve farmers’ livelihoods.

The agriculture and food sector is experiencing digital transformation due to its omnipresence and mobility. For farmers of all sizes, access to information and markets is enhanced. Production and productivity are increasing, and supply chains are being streamlined, all thanks to the spread of mobile technology, remote-sensing services, and distributed computing. 

The use of precision agriculture, data analytics, and other technologies are helping farmers optimize crop yields, reduce costs, and improve sustainability. Developing digital infrastructure and creating partnerships to enable the widespread adoption of these technologies will be critical for the future of agriculture. 

Partnerships are also important because digital transformation requires collaboration between different stakeholders, including farmers, researchers, technology providers, policymakers, and financial institutions. Partnerships can help facilitate the sharing of knowledge and resources, develop standards and regulations, and create a supportive ecosystem that encourages the adoption of digital technologies.

Digital transformation in agriculture has much potential to improve sustainability. Using data-driven decision-making, precision agriculture, the Internet of Things, and machine learning to optimize production and minimize environmental impact can be very influential. These technologies even have the potential to improve food security and reduce poverty through increasing productivity. 

In one case study, precision agriculture was used to optimize the nitrogen fertilization of wheat. Through digital technologies, the study authors found the optimized balance of applying the right amount of fertilizer to reach full yield potential without any potential environmental challenges. This is one example of digital transformation in agriculture moving the industry toward increased sustainability. 

Agronomic Field Trials for Future Innovation 

Decisions make themselves when enough is known. In agriculture today, it’s about knowing as much as possible, as fast as possible to move quickly to market. Field trials support this goal, but field trial processes can be enhanced through data analytics tools. 

Field trials enable companies to answer key questions about product markets, effectiveness, environmental impact, safety, or efficacy. Agriculture’s seasonality and time-sensitive nature mean every season is an important opportunity to gather as much data as possible – and analyze it quickly, to support decisions before the next in-season opportunity to refine or sell.

Maximizing the potential of field trial data insights will greatly accelerate the production of agricultural innovation outputs. Companies can move quickly and with confidence when they’re equipped with the most accurate information about product performance and they get that information as quickly as possible. As the data flow around field trials increases in quality and pace, the overall process of bringing meaningful innovation to market increases, too. 

Digital tools also provide a host of other benefits, such as optimizing agricultural research and development efficiency, increasing data collaboration and interoperability, and even ensuring the integrity of data in mobile field trials.   

Digitization improves agronomic field trials specifically in the analysis space by providing data in real-time to collaborators, enhancing data quality, and using AI to drive efficient analysis. Data analytics tools even allow current trial data to be supplemented with legacy data to expand the reach of the study and increase confidence. This is only possible through digital transformation and leads to efficient innovation to improve yields. 

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Agmatix and Agricultural Field Trial Data Analysis 

Finding the right data analytics tools to digitize your field trial process can make all the difference in agriculture. 

Agronomic Trial Management is an agriculture experiment data gathering tool that serves as an end-to-end solution for planning, managing, executing, and completing data analysis in agriculture field trials.

Enhanced field trial data management enables researchers to collaborate quickly across teams and make fast decisions based on data analytics. The cutting-edge technology provides full visibility and control of the field trial, supports the standardization of protocols and data collection, and even has extended mobile capabilities to support on-farm experiments. 

Data analysis is critical in agronomic field trials. The Agronomic Trial Management platform supports successful trial data analysis. Users can monitor outliers and validate data on an ongoing basis throughout the trial. The analysis is supported across treatments or collection dates, so it’s possible to track trends over time. Visual interfaces support fast decision-making between cross-functional teams.

The Agmatix platform is supported by Axiom, the data warehouse engine that unlocks the potential of data through ingestion, enrichment, standardization, and harmonization. This enables the use of agronomic databases in a variety of research applications using new and legacy data. Axiom’s important functionality enables Agmatix to bring quality data solutions to increase speed to market and boost agricultural output.  

Through these innovative tools, Agmatix is leading the digital transformation in agriculture with the intent to support sustainable practices that increase yields and protect natural resources. Armed with data analytics tools in agriculture, industry professionals can lead successful field trials and help farmers make decisions at the field level to grow yields. 

Data-driven intelligence integrated within field trials has the opportunity to boost output by shortening the discovery time frame. Through digital transformation, agronomic field trials can become a low-risk step in proving and maximizing product performance to bring important innovations to the market as quickly as possible. 

Revolutionizing Field Trials: Unleashing the Power of Advanced Cloud-Based Solutions

Agricultural field trials play a crucial role in the process of researching and developing new agricultural innovations. However, in the past, these trials were carried out in isolated environments using outdated on-prem trial systems. To illustrate the drawbacks of this approach, consider the following anecdote about the traditional methods of conducting field trials.

Meet Anna, a seasoned trial coordinator who is currently working with a global team on a complex field trial to evaluate the efficacy and safety of a new biostimulant. With over a decade of experience in the field of agriculture, Anna brings a wealth of knowledge and expertise to the project. Her role in the trial is to oversee the coordination and management of the study, ensuring that all aspects of the trial are conducted in a timely and efficient manner. With the potential of this new biostimulant to revolutionize the agriculture industry, the trial holds great significance, and Anna is dedicated to ensuring that the study is conducted to the highest standard.

Once upon a time, Anna would be on a team of researchers set out to conduct a field trial to evaluate the efficacy and safety of a new biostimulant. The team consisted of trial coordinators, researchers, and field technicians from different parts of the world. They faced several challenges right from the planning stage, which mostly were a product of using legacy-based on-prem field trial systems.

First, collaboration was a significant hurdle. The team found it challenging to get the most up-to-date field trial plans approved due to time differences and communication barriers. The trial coordinator spent countless hours on emails and video conferences trying to bring everyone on the same page, but the process was cumbersome, and the team fell behind schedule.

On the day that the trial was set to begin, the team arrived on-site, ready to commence work, but the weather had other plans. Unpredictable weather patterns made it difficult to execute the planned treatments, forcing the team to make on-the-fly adjustments. The team had to change their plans and make adjustments to the trial protocol to ensure that the results remained accurate.

To make matters worse, a new team member joined the trial, and the on-prem complex data collection system required hours of installation time. The trial coordinator had to find time to onboard the new team member, delaying the start of the trial. For data collection, the team had to rely on pen and paper, which made data collection slow and error-prone. The team encountered several errors during the trial, which they only identified late. Manual data entry after the collection was tedious, time-consuming, and posed a risk of errors.

Despite these challenges, the team persevered, and the trial eventually concluded. The data collected was analyzed, and the team discovered valuable insights about the efficacy and safety of the new biostimulant. However, the experience taught the team a valuable lesson: they needed a better way to plan, manage, execute, and analyze their field trials.

The Agronomic Field Trial: Reimagined

As the trial coordinator for a complex field trial aimed at understanding the efficacy and safety of a new biostimulant, Anna faced numerous challenges. Planning, executing, and analyzing the trial was a time-consuming and resource-intensive process that required a great deal of manual decision-making and analysis.

However, with the introduction of next-generation, cloud-based agronomic trial management software like Agmatix Agronomic Trial Management, Anna is now able to streamline many of the processes involved in the trial. The software allows her to drag and drop to design a professional field trial, collaborate with other stakeholders and share status updates, and even keep track of tasks.

The potential of the trial could be unlimited with the right data-based, AI-driven technologies that accelerate time to market and speed to critical decisions. And that’s where Agmatix comes in. The platform automatically ingested data – including legacy trial data – for cross-trial analysis. It automatically created actionable reports and recommendations and used pre-built statistical analysis to build models from the data quickly.

Collaborating with other stakeholders, regardless of geographical location, is seamless within the platform. And now the data-driven insights and agronomic modeling unlock a new, deeper understanding of the trial. Anna is able to take the data even further, creating predictive crop models that maximized yields. With Agmatix, she is also able to quickly create the reports needed for regulatory approvals.

The potential of how Anna and her team approach field trials is now unlimited, thanks to the right data-based, AI-driven technologies that accelerate their time to market and speed up critical decisions. With Agmatix Agronomic Trial Management, Anna is able to optimize the trial and gain valuable insights that would have otherwise been impossible to obtain. She is excited to see what the future holds by adopting this groundbreaking technology and the possibilities it holds for the agriculture industry.

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Limitless Opportunities with Next-Generation Field Trials 

To summarize, the agricultural industry faces significant challenges, including feeding a growing global population, addressing food scarcity, and reducing its carbon footprint in the face of a changing climate. The development of sustainable and efficient crop cultivation methods and new innovations is crucial to meeting these challenges. 

As the leading R&D trial platform, Agmatix’s cloud-based agronomic trial management software enables companies like Anna’s to maximize product potential and mitigate downstream risks with data-driven intelligence. 

Innovation starts with Agmatix! The Agmatix platform increases data interoperability, provides easy access, and enables data reuse across the organization for better collaboration and knowledge discovery.

Critical Factors Driving Trends in Field Trials Today

Over the years, field trials have become a fundamental component of agriculture research and development. With ever-evolving production practices and products, it’s critical to test them in real-world scenarios to evaluate their efficacy and safety. Today, agriculture professionals and farmers conduct approximately 150 million field trials annually to collect valuable data.

Field trial data is a powerful tool that helps researchers understand product performance, safety, and market positioning. Furthermore, it plays a crucial role in addressing the challenges faced by the agriculture industry and society at large.

As we look ahead, field trials will remain a cornerstone of agricultural research. In this blog, we will explore the key trends shaping the future of field trials in agriculture.

Five Ways Field Trials Fuel Future Innovation

1. Optimizing Efficiencies 

Data collected from field trials is crucial to optimizing Agricultural R&D efficiency. Field trials can increase innovation by making data collection more efficient. 

Data collected during field trials is often vast, complex, and heterogeneous. By using IoT sensors, automated data capture field trial software, and other agriculture field trial tools, data collection can be standardized and sped up. This cuts down on human error and makes collected data more accurate and complete. This also enables companies to make more informed decisions about product development, marketing, and commercialization.

Manage and control technical trial operations

Advances in agricultural field trial tech also help manage and control technical trial operations. By efficiently deploying standard operating procedures and protocols, field trials can be executed consistently, reducing variability and improving the reliability of the results. This ensures that the data collected is of high quality, and the products tested are safe, effective, and compliant with regulatory requirements.

Reduce the time and effort required for data wrangling and analysis

Another advantage of leading tech in ag field trials is less wasted time spent wrangling excel sheets between systems and preparing data for analysis. By using integrated systems that automate data transfer and analysis, the data collected during field trials can be easily analyzed and visualized, saving time and effort. This allows the company to focus on deriving insights from the data and making informed decisions about product development, marketing, and commercialization.

Efficient management, control, and monitoring of field trials

The Agmatix platform drives major advances in agricultural field trial tech and optimizes efficiencies. Field trial software helps to manage, control, and monitor more efficiently with task management capabilities. The platform also allows for simple data collection form configuration, allowing for standardized and streamlined data collection. Data collection protocols ensure consistency, increasing the accuracy and completeness of the data collected.

Enhanced efficiency through mobile app 

A data collection mobile app improves the efficiency of field trials by allowing for real-time data capture and reducing human error. The cloud-based system integrations allow for seamless data transfer and analysis, saving time and effort on data wrangling and analysis.

Centralized location for data visualization and analysis

The insights model within the Agmatix platform provides a centralized location for data visualization and analysis, allowing for data-driven decision making. Additionally, the platform’s roadmap includes an AI recommendation engine, which has the potential to further optimize field trial efficiencies by providing intelligent recommendations for trial design.

2. Increasing Data Integrity

Field trials are an integral part of agricultural research and development, providing critical data that is used to optimize agricultural products and practices. However, the accuracy and integrity of data collected during field trials can be compromised by a range of factors, including errors in data entry, inconsistent data collection protocols, and delays in data validation. 

To address these challenges, advances in agricultural field trial tech enable real-time data collation and validation at the trial level which increases the integrity of collected data by reducing the likelihood of errors and inconsistencies. By leveraging modern technologies such as IoT sensors, mobile data capture, and other agriculture field trial tools, data can be collected in real-time, reducing the time and effort required for data entry and improving the accuracy and completeness of the data collected.

Furthermore, real-time data validation at the trial level can assist in identifying errors or inconsistencies in data as they occur, allowing for immediate corrective action. This reduces the vulnerability of collected data to errors and inconsistencies, which can have an impact on subsequent analysis, insights, and reporting.

By utilizing advanced field trial technologies that enable real-time data collation and validation, agricultural research and development organizations can increase the accuracy and integrity of their field trial data. This, in turn, leads to more accurate and reliable insights and recommendations, improving the efficiency and effectiveness of agricultural research and development.

Agmatix is leading advancements in agricultural field trial tech and offers a range of capabilities that improve the accuracy and integrity of field trial data. These capabilities include easy configuration of data collection forms, predefined data collection protocols, a mobile app for data collection, data visualization and validations, and error handling.

With easy configuration of data collection forms and predefined data collection protocols, data can be collected in a standardized and streamlined way, reducing the likelihood of errors and inconsistencies. The mobile app for data collection enables real-time data capture, reducing the time and effort required for data entry and improving the accuracy and completeness of collected data.

Agmatix’s data validations and error handling capabilities enable users to identify errors or inconsistencies in data as they occur, enabling corrective action to be taken immediately. The platform also uses its own GUARDS data standard ontologies to standardize the collected data and ensure it’s consistent and compliant with industry standards.

In addition to data validations and error handling, Agmatix also offers trial insights that provide a centralized location for data visualization and analysis, enabling data-driven decision making. 

Finally, Agmatix’s cloud-based solution offers real-time data collection visualization, allowing stakeholders to monitor field trials via desktop, tablet, and mobile applications. This ensures accurate and consistent data collection throughout the trial.

Overall, Agmatix’s capabilities in advanced field trial technology are designed to increase the accuracy and integrity of field trial data, reducing the likelihood of errors and inconsistencies that can impact later analysis, insights, and reporting. With these capabilities, agricultural research and development organizations can improve the efficiency and effectiveness of their field trials, leading to more accurate and reliable insights and recommendations.

3. Data Collaboration and Interoperability

Technology has made it possible to increase data collaboration and interoperability in agricultural field trials. Improved trial data stewardship leads to better knowledge discovery and innovation, which is critical for advancing agricultural research and development.

One of the key advancements in field trial technology is the increase in data interoperability between data sets. By utilizing standardized data formats and protocols, different data sets can be easily combined and analyzed, leading to new insights and discoveries. 

This also allows trial owners to easily share data access with multiple stakeholders, enabling researchers, agronomists, and other professionals to access the same data sets and collaborate on research and development projects.

Moreover, advances in field trial technology have enabled the reuse of data across the organization to improve collaboration. By leveraging modern technologies such as cloud-based data storage and sharing platforms, data can be easily leveraged across different departments and teams, enabling researchers and other professionals to access and use the same data sets for cross-trial analysis. 

The Agmatix platform plays a significant role in increasing data collaboration and interoperability in agricultural field trials. One of the key capabilities of the Agmatix platform is its ability to provide a multi-stakeholder view of a single trial and its analysis. 

This means that researchers, agronomists, and other professionals can access and analyze the same data sets based on the permissions set by the organization’s trial administrator. This makes it easier for people to work together and reduces the chance of mistakes or inconsistencies.

The platform also offers insight workspaces with data collaboration and sharing capabilities, enabling stakeholders to work together on research and development projects, share insights, and collaborate in real time. This feature facilitates data collaboration and interoperability by providing a central location where stakeholders can access and analyze data sets.

Agmatix also uses its GUARDS data standard ontologies to ensure that collected data is standardized, which increases data interoperability between different data sets. This helps researchers and other professionals to combine and analyze different data sets more easily, leading to new insights and discoveries.

Furthermore, Agmatix’s platform includes the Axiom data lake, a cloud-based storage and sharing platform that provides secure data storage and facilitates data reuse across the organization for better collaboration. This feature ensures that data can be safely shared across different departments and teams, allowing stakeholders to access and utilize the same data sets.

4. Risk Reduction for Field Trial Operators 

Technology is essential for reducing risk in agricultural field trials by identifying data collection issues, outliers, and sensor defects during the trial process. Advanced data analytics and machine learning algorithms enable trial operators to detect and address problems in real time, mitigating major data collection errors or inaccuracies.

Leveraging historical data with machine learning algorithms helps optimize trial operations, reduce the risk of failure, and avoid the need to replicate trials based on findings already leveraged from historical data. Utilizing cloud-based services reduces the cost and complexity of managing IT infrastructure and allows easier integration between systems, reducing customizations over time.

The Agmatix platform provides field trial operators with executive dashboards for real-time visibility into trial operations and data, including advanced analytics capabilities to identify trends and patterns for optimizing operations and improving outcomes. Features to exclude anomalies and outliers and tools for data validation and error handling ensure accurate and reliable data.

The digital twin feature, an upcoming addition to the Agmatix platform, creates a virtual model of the field trial environment, allowing operators to test and optimize different scenarios before implementing them in the real world.

As a cloud-based and flexible software-as-a-service (SaaS) solution, the Agmatix technology platform offers field trial operators a powerful tool for managing and optimizing their operations. It provides them with the information needed to make informed decisions quickly and effectively.

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Revolutionizing Field Trials: Unleashing the Power of Advanced Cloud-Based

Going Digital: The New Generation of Field Trials

As agriculture continues to move towards digitalization, technology is playing a more important role than ever in field trials. With the tap of a tablet or cell phone, we can leverage leading tech to increase efficiency and accuracy. Cloud-based software-as-a-service (SaaS) solutions, web-based platforms, and mobile apps make it easy to plan and map field trials, collect data, and communicate with others involved in the trial. By utilizing a single centralized platform, collaboration becomes seamless and efficiency is increased.

Agmatix understands the challenges of planning and executing field trials and the importance of impactful data. That’s why they offer an Agronomic Trial Management solution with end-to-end capabilities that support planning, executing, analyzing, and managing field trials. Their mobile application, with online and offline capabilities, supports field trials from anywhere, making it easier to identify errors and data gaps sooner and keep the trial data collection on track.

The results from agriculture field trials powered by precision farming tools will inform innovation that can address food scarcity, feed a growing population, and better manage agriculture’s carbon footprint. Companies must increase the pace and efficiency of agriculture field trials to remain competitive and bring new products to market that will improve sustainable agriculture.

As technology continues to advance in the agricultural field trial industry, it will bring greater efficiency to these important efforts and unlock their true value. With its cutting-edge technology tools and solutions for ag field trials, Agmatix is committed to helping its customers extract actionable insights at the field level.

The cloud-based ag data train is about to leave the station – are you on it?

In order to meet the ever-increasing consumption needs of the global population, agriculture businesses are modernizing through smart agriculture based on cloud computing and IoT technologies. These technologies create solutions for the effective usage of finite resources like arable land and water. 

These technologies can be used to remotely monitor soil moisture and crop growth and to take preventive actions to identify crop damages and dangers. This makes it possible for farmers to engage in “Smart Agriculture,” which involves using new technologies based on cloud computing and IoT to remotely manage and automate agricultural tasks. 

Smart agriculture creates a vast amount of data on the farm, every day. The average estimated number of data points generated on the farm has over doubled between 2012 and 2022. By 2034, an estimated 4 million data points will be generated on the average farm, every single day. That vast amount of data requires top-notch data tools to manage and unlock its full potential. Without proper data support, all of those valuable data points generated on the farm will never contribute to agriculture in the meaningful way they need to. 

Today, data is used for some applications on the farm. According to a Purdue University survey, 93% of farmers are using data to support fertilization decisions, with 71% specifically using variable rate technology for fertilizer application. Only 7% of farmers surveyed reported that they do not collect any farm data.

Of those who do collect data, 58% are sharing it with an agronomist to support decision-making. This means that farm data accuracy with cloud-based software in agriculture is imperative to success.

The role of cloud computing technology in agriculture fields and the use of big data analysis can lead to increased innovation, improved business resilience, and greater profits. According to a report by the Enterprise Strategy Group (ESG), businesses that effectively harness and leverage data are more resilient and profitable than those that don’t. Data leaders are more likely to identify and remediate security incidents quickly, making better cloud-based farming decisions, and deriving more revenue from data monetization. 

Agriculture’s Need for Cloud-Based Technology 

Applications of Agricultural Data

Agricultural data has a wide range of applications that can transform farming practices and contribute to enhancing food security. The use of advanced technologies in agriculture generates a large amount of data, known as big data, which can be analyzed to make better farm-level decisions. 

Sensors, software-based decision support systems, and digital communication tools are identified as critical technologies for data-driven agriculture. Additionally, artificial intelligence complements big data by enabling data mining and extracting meaningful value from raw data. 

Yield prediction algorithms, image recognition algorithms for pest and disease detection, and robotics for crop harvesting are among the AI applications being developed in agriculture. The deployment of digital decision-support tools, big data analytics, and artificial intelligence has the potential to improve agricultural productivity and contribute positively to agricultural machinery and logistics, market information, plant breeding, risk management, and sustainability.

The agriculture industry is facing increasing demand and various disruptive forces, including constraints in land and farming inputs, rising costs of inputs, and the need to improve sustainability and resilience. Connectivity and advanced digital tools are needed to address these challenges and enable the next productivity leap. If implemented successfully in agriculture, connectivity could add $500 billion in additional value to the global gross domestic product by 2030.

Cloud Computing Applications Win in Agriculture 

Cloud computing applications in agriculture have revolutionized the field in recent years. Across the industry, cloud-based technologies give companies the opportunity to improve their operations to gain a competitive edge. Taking that first step away from on-prem and towards cloud computing is a critical juncture for companies that are looking to grow in capability, innovation, and scale. 

Cloud computing

  1. Reduces initial costs for agribusinesses. Instead of purchasing expensive software and hardware, the necessary space to store them, and hiring the staff to support them, companies can simply subscribe to cloud-based solutions. This gives them the flexibility to manage their business and enables them to only pay for what they need. Companies can reduce their overall capital expenses.
  1. Offers limitless scale and resource allocation as needed. Agribusinesses can easily increase or decrease their computing resources to meet their changing needs. This scalability is particularly useful during peak periods such as planting or harvest seasons. It also allows companies to grow and innovate faster, without computing infrastructure holding them back. 
  1. Takes care of back-end maintenance and upgrades, eliminating the need for hands-on, resource-intensive maintenance. Companies can focus on their core competencies and leave the IT management to the cloud service provider. This also improves data security. 
  1. Enables easy and rapid development. Research and development teams can quickly test and deploy new applications, allowing them to respond quickly to changing market conditions.
  1. Team collaboration is made easy with cloud computing. Team members can collaborate on the same data and system in the cloud, regardless of their physical location. This improves communication and allows for better cloud-based farming decision-making. And because cloud computing allows data to be viewed and analyzed in real time, teams can make in-season and time-sensitive decisions with ease. 
  1. Finally, cloud computing enables global development. Companies can leverage cloud-based solutions to expand their operations across the globe. This is particularly useful for small-scale or start-up organizations that may not have the resources to expand their operations on their own. Cloud computing provides access at any scale. 

Altogether, these six factors influenced by cloud computing support accelerated innovation in agriculture at a critical time when new approaches are needed to adapt to net zero goals and growing populations. 

Cloud computing has many applications in agriculture and offers a wide range of benefits to companies in the agriculture industry. By leveraging cloud-based agricultural technologies, companies can reduce costs, increase efficiency, and gain a competitive edge in the market. 

In agriculture specifically, there’s an urgent need to adopt cloud-based farming decision technologies because agricultural data is expected to be stored for 10-30 years – eventually exceeding 100 petabytes. Using cloud computing applications in agriculture to increase access to this vast dataset will increase collaboration between experts to unlock the true value of the data. 

Are You On the Cloud-Based Data Train? 

Cloud computing technology’s role in agriculture fields offers numerous benefits to various players in the industry. Without adopting cloud computing and IoT to support smart agriculture, companies will be making decisions and operating based on outdated on-prem systems that will hold them back from their true potential. 

For agronomists, cloud-based technology can help optimize crop yields and reduce waste by providing real-time data on soil health, weather patterns, and other critical factors that impact plant growth. This provides a competitive edge to build their relationships with growers and their customers. 

Agriculture input companies can leverage cloud-based platforms to streamline their operations, track inventory, and better manage their supply chains. Through cloud-based data and IoT, input companies can support farmers in smart agriculture and making product-related decisions based on data and models. By finding the best fit for the farmer, the farm, and the environment, input companies will win with cloud-based farming decision-making. 

Researchers and scientists can use cloud-based platforms to access and share data from various sources, collaborate with colleagues, and accelerate the pace of scientific discovery. Researchers can work in tandem on a live dataset, increasing the speed at which they arrive at the answers. 

Finally, food and beverage companies can leverage cloud-based platforms to track data from raw food materials, improve supply chain transparency, and promote sustainability. Cloud computing allows companies to track data across continents and companies as raw food materials are grown, harvested, and then transitioned down the supply chain until they are manufactured into food goods. 

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Agmatix Is On Board for Smart Agriculture 

Agmatix is a next-generation company. We offer smart agriculture solutions based on cloud computing and IoT that support agriculture professionals in achieving goals related to their businesses and sustainability. 

Agmatix leads the industry with Data-driven ag solutions that provide access to new data. Through open-source databases such as the Global Crop Nutrient Database, Agmatix supports access to open-source data that can be used with cloud computing to develop new innovations. 

Agmatix knows the value of collaboration in developing new innovations and solving big challenges. That’s why the backbone of our work is Axiom technology, which breaks down data silos and standardizes data to be used together – regardless of source. Axiom is the backbone of Agmatix technologies that unlock the true potential of data. 

One of those technologies is the Agronomic Field Trial platform. It’s an end-to-end solution for agronomic field trial management, supporting front-end planning, execution, and analysis. It provides both modern reporting and mobile data collection opportunities that meet the needs of those working in today’s data-driven agriculture industry. These features are only possible because of cloud computing. 

Digital Crop Advisor is a decision support system that builds custom, site-specific crop nutrition recommendations. It uses AI recommendations driven by cloud-based technology to support agronomists in providing recommendations to customers that optimize crop yield while minimizing the impact on the environment. Digital Crop Advisor’s unique approach even provides insights into sustainability KPIs – all through cloud computing. 
Agmatix is poised to revolutionize the agriculture industry using cutting-edge cloud-based farming decision-making technology to optimize crop production and drive sustainable growth. Agmatix will keep innovating, but the cloud-based data train is about to leave the station. Companies making the jump from the on-prem platform will reap the benefits of increased innovation and speed to market.

Next Generation Field Trials are Data-Driven

Agriculture relies heavily on science, with soil science, plant physiology, chemistry, climatology, and biology all playing important roles in achieving successful agricultural production. Field trials, also known as experimentation, have been integral to agricultural innovation for nearly two centuries, dating back to before the Green Revolution and the Industrial Revolution. Today, over 30,000 farms worldwide participate in on-field experiments, conducting around 150 million experiments annually and analyzing 2 million field trials each year.

Researchers use field trials to assess product efficacy, identify optimal conditions for performance, and explore future developments, making them a crucial driver of innovation within the industry. On-farm field trials, also known as “on-farm experiments,” allow farmers to test new products or production methods in the same setting where they would be used on a large scale, reducing potential risks. By continually experimenting and conducting field tests, farmers gain valuable insights into their land and can increase productivity year after year.

However, not all field trials are created equal. Next-generation, data-driven agriculture field trials will accelerate innovation, promote collaboration among stakeholders, and foster more sustainable farming practices. 

Field Trials of the Future 

Field trials are evolving in tandem with agriculture technology. When it comes to next-generation aspects, the fundamental principles of field trials will be retained. However, the outcomes and effectiveness will go further than ever before in supporting decision-making. Next-generation field trial technologies are paving the way for more powerful, collaborative, and effective field trials while building on today’s foundation of field trial success.

This will require researchers and agriculture professionals to abandon on-prem ag field trial platforms and utilize cloud-based, next-generation solutions. This shift will create limitless opportunities.

Instead of on-premises or legacy systems, cloud-based software is used to manage and run field trials for the next generation of agriculture. Users benefit from continuous improvement, scalability, backups, and simple configuration with this project management capability, which requires no installation and little onboarding. Managerial dashboards make project management tasks like annual planning, task management, and reporting simple and efficient to complete.

Next-generation field trial technology provides an efficient but adaptable platform for on-farm experiments. APIs are used to integrate with external data sources and interact with the environment. The system can connect to IoT sensors, spatial data, weather data, and other sources. Furthermore, global control with local configurations allows for easily customized experiences without involving developers or coding.

With next-generation field trial technology, a data-based approach is used, leveraging the data to drive innovation rather than focusing on the process. In agricultural field trial design, one way to do this is to use treatment combinations based on data to make sure the results are accurate from the start.

In next-generation trials, data collection takes on new meaning with mobile capabilities that enable timely, accurate, and secure data collection. Online and offline capabilities automatically sync with web app configuration, allowing for unlimited data collection and use.

Collaboration has always been an important part of field trials, and new technology that connects stakeholders in a unified platform will increase efficiency in trial planning, data collection, and analysis. Efficiency gains can be enjoyed both internally and externally with key partners through trial workspace sharing, task assignments, and better reporting tools. Next-generation field trial solutions make the user experience flexible for all trail contributors and allow the trial owner to have better visibility into trial operations and results. 

Agmatix Fuels Field Trial Innovation 

The Agronomic Trial Management solution enables next-generation agriculture field trials and fuels the development of new solutions to agriculture’s most pressing challenges. This digital, cloud-based, AI-driven solution offers a comprehensive planning process that enables users to conduct one-of-a-kind trials based on hundreds of customizable treatment combinations.

Users can see the status of the trial in real-time thanks to dashboards that are easy to use with clear communication channels that let trial owners, researchers, field technicians, or third-party contract labs like CROs work together on trials. Managing in-field data collection tasks and sharing data results in real-time ensures trial validity. Success becomes second nature when combined with protocol adherence. A next-generation mobile application delivers the best data management and collection benefits to handheld devices and more collaborators than ever before.

Data collection can be changed to fit the needs of the user and protocols. To detect outliers or anomalies, data can be viewed and validated in real-time. Furthermore, trial data can be easily shared in the platform stakeholders or exported to reports.

When the in-field aspects of the trial are finished and it’s time to dig into the trial results, Agmatix makes it simple to analyze and compare the results by utilizing pre-built statistical widgets. Agmatix’s AI-driven engine standardizes agronomic data and turns it into powerful insights.

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Field Trials for Future Generations

Agriculture needs data-driven, next-generation solutions that speed up and improve innovation cycles, which are built around field trials. New technologies open up an infinite amount of data that can be used to push agriculture beyond where it has been before. Agmatix is committed to supporting researchers, agronomists, and growers with strategies for field trials that are data-driven and sustainable.

The New Generation of Agronomists: Pushing to Net Zero Carbon Footprint

Agronomy has long been the bedrock of agricultural crop production. Crop, soil, and plant sciences have fueled innovations and increases in crop yields for centuries. American universities began incorporating agronomy studies over 100 years ago, formalizing the science to support plant use for food, fuel, fiber, and conservation. Agronomists have had a massive impact on global well-being and play an important role in supporting farmers. They consult and help educate farmers on products and production practices that could be a good fit for their operations, oftentimes, as agricultural companies advisors who support research or sales initiatives. 

In the future, agronomists’ opportunity to influence and impact will only grow. Connecting plant and soil science, environmental science, and best practices with the growers who can implement them will become increasingly important as agriculture strives to reach net zero emission of carbon while feeding a growing population. Agriculture is challenged with reducing its carbon footprint while simultaneously grappling with a production environment that’s evolving due to climate change. 

Agronomists have a unique opportunity to drive sustainable agriculture and position farmers to adopt next-generation technologies that will improve crop productivity while lowering agriculture’s carbon footprint. 

Net Zero Carbon Footprint 

Carbon footprint refers to the cumulative greenhouse gasses that are generated by a given set of actions. Common greenhouse gasses include carbon dioxide and methane and can be generated by everyday actions such as driving a car or drying clothes in a clothes washer. 

Addressing greenhouse gas emissions is critical for curbing the effects of climate change and ensuring the planet will be habitable in the future. Reaching net zero by 2050 is necessary to keep global warming at a level that will prevent the most devastating effects of climate change. Many countries have a net-zero target, though currently, the global population is not on track to reach net zero by 2050. In fact, global greenhouse gases are projected to rise by 10% by 2030.  

Net Zero Emission of Carbon in Agriculture 

Reaching net zero carbon emissions to curb the worst effects of climate change requires every industry to do its part in reducing – and eventually negating – their carbon footprint. Agriculture is no different – in fact, it has a strong role to play in reaching net zero emissions of carbon. 

The agriculture industry is one of the primary sources of greenhouse gas emissions. A United Nations estimate found the agriculture industry, including its supply chain, contributed 16.5 billion tonnes of greenhouse gases in 2019. 7.2 billion tonnes of that came directly from the farm. 

In total, nearly one-third of human-caused greenhouse gas emissions come from global agri-food systems. In the United States, the Environmental Protection Agency estimates that agriculture contributed 11% of the country’s greenhouse gas emissions in 2020. 

Changes to farming practices can make a real difference in agriculture’s greenhouse gas contributions. By choosing greenhouse gas efficient technologies and practices, farmers can reduce greenhouse gas emissions by an estimated 20% by 2050.

Those practices include reducing the over-application of nitrogen, variable rate fertilization, dry direct seeding, reduced or no tillage production systems, precise fertilizer timing, controlled release fertilizers, improved rice fertilization and improved rice paddy water management. 

Adopting these production practices and technologies isn’t always a straightforward replacement for the current practice. That’s where new-generation agronomists come in – as  key players in working on how to reduce carbon footprint in agriculture.  

Agronomists’ Opportunity to Drive Net Zero Emissions Home 

Agronomists play a key role in farmer adoption of new technologies – from controlled release fertilizers to variable rate fertilization and beyond. In many cases, they will be the ones to write prescriptions for variable rate fertilization, identify the precise growth stages for fertilizer timing, or help define a no-till production system for a farmer. 

Armed with the best tools, new-generation agronomists will lead the way in helping farmers determine how to reduce their carbon footprint in agriculture. Their influence with farmers combined with the vast amounts of data generated in agriculture and the digital tools available to them create the perfect opportunity for massive impact.

Agmatix is dedicated to supporting new-generation agronomists in maximizing their impact by helping farmers improve yields and crop quality while reducing their carbon footprint. Digital Crop Advisor specializes in using real-time data to customize crop nutrition, so crops can reach their full potential with minimal environmental impact. 

Through this decision support system, agronomists can access tailored crop nutrition optimization with unique, data-driven production recommendations. Digital Crop Advisor is the definition of enhanced crop protocol management, including recommendations for over 150 crops and 12 nutrient data profiles. 

But Digital Crop Advisor is more than just optimized nutrition. Sustainability is the backbone of the platform, enabling new-generation agronomists to rely on it with confidence as they work with farmers to reduce agriculture’s carbon footprint. It’s a true carbon footprint optimizer for agriculture. Sustainable nutrient recommendations are included with each plan, created based on the carbon footprint analysis of the plan. 

Agronomists can also go deeper into sustainability with Digital Crop Advisor. Simulations can be run on various scenarios to compare recommendations and understand tradeoffs between yield and environmental impact. Controlled release fertilizers – one of the key technologies that can reduce emissions – can be selected within the system. And the algorithm automatically adjusts crop nutrition needs to prevent over-fertilization. This science-based approach improves both the grower and environmental outcomes. 

Digital Crop Advisor includes an agriculture carbon footprint calculator that helps users to understand the carbon footprint rate for different nutrition plans. Based on field characteristics like soil type, pH, and organic matter as well as environmental conditions, agronomic practices, crop type, fertilizer type, application timing, and residue management, the system can determine greenhouse gas emissions and carbon footprint. This tool is instrumental in helping agronomists lead farmers toward sustainable approaches and a net zero future. 

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The New Generation of Agronomists Leads the Way 

Agronomists have always been critical for driving product and production practice adoption on farms. In the 21st century, agronomists will carry the flag of net zero at the field level. Agmatix isn’t just cheering them on, but supplying them with the tools they need to confidently and effectively lead farmers to net zero emissions. 

The Benefits of Ag Cloud-based Solutions Over Legacy Systems to Empower Crop Growth and Sustainability

The shift to cloud computing away from legacy systems has had significant implications for data management, operational effectiveness, communication, and collaboration. With cloud computing, organizations can store and access large amounts of data from anywhere, at any time, and on any device.

Advanced Agriculture cloud-based solutions have greatly streamlined data management processes and reduced the need for expensive in-house data storage infrastructure as is still the case with legacy on-prem tech.

Additionally, applying cloud computing in Agriculture has improved operational effectiveness by allowing organizations to easily scale their computing resources as needed, reducing downtime and increasing efficiency. 

Agriculture cloud-based solutions can empower crop growth and sustainability in several ways:

  1. Precision Agriculture: By collecting and conducting data analytics on weather conditions, soil characteristics, and crop health, cloud-based solutions can provide farmers with insights into how to optimize their crop growth. This can include determining the ideal time to plant when to apply fertilizer and pesticides, and what crops to plant in each field.
  2. Remote Monitoring: Advanced cloud-based solutions in agriculture enable growers to keep track of crop health and soil conditions in real time. This can help identify potential issues early, allowing farmers to take corrective action and improve crop yields. Cloud-based solutions allow farmers to monitor their fields remotely.
  3. Supply Chain Management: By connecting farmers, suppliers, and buyers, cloud-based solutions can help streamline the supply chain and reduce waste. This can result in more efficient use of resources and reduce the environmental impact of agriculture. 
  1. Decision-Making: Ag Cloud-based solutions provide farmers with access to large amounts of data, including market prices and crop yields. This data can be used to make informed decisions about planting, harvesting, and marketing their crops, improving sustainability and profitability.
  2. Predictive Analytics: By analyzing historical data, cloud-based solutions can predict future crop yields and help farmers make informed decisions about planting, harvesting, and marketing their crops. This can help improve sustainability and reduce waste by reducing overproduction and waste.

Agriculture cloud-based solutions can empower crop growth and sustainability by providing farmers with the tools and information they need to make informed decisions and optimize their operations.

Last but not least, Ag cloud-based solutions have facilitated communication and collaboration by providing access to shared resources and tools that enable teams to work together more effectively, regardless of location or time. 

Overall, cloud computing has been a transformative technology that has had far-reaching implications for the way organizations manage data, operate, and collaborate with one another.

Ag Cloud-Based Platforms Capture New Capabilities 

The shift to cloud computing has greatly impacted various aspects of data management, operational effectiveness, communication, and collaboration. The cloud offers real-time data access, cost savings through reduced capital investment and server maintenance, automatic data backups, scalability, easy configuration, API integration, and customizability. 

These features make it an attractive option for growers looking to streamline their operations and improve their overall efficiency, while also reducing the risk of data loss. 

Additionally, the cloud enables quick onboarding, enhanced security, and easy scalability, which allows organizations to grow and adjust their resources as needed. The use of cloud technology has therefore become a transformative tool in the context of Agriculture cloud-based solutions which has been seeking to replace legacy on-prem tech for the past few years. This has had far-reaching implications for the way organizations manage their data, operate, and collaborate with one another.

Benefits of Cloud-Based Solutions in Agriculture

Just as steam power technology spurred the industrial revolution, digital advancements in agriculture are fueling the agricultural revolution of the 21st century. In the world of agriculture, the adoption of cloud-based solutions has the potential to revolutionize the way big data is utilized. 

By centralizing critical information such as soil conditions, land information, marketing data, weather patterns, crop and pest management, and agro informatics in a cloud-based platform, a comprehensive overview of the entire agricultural ecosystem can be achieved. 

With the added capabilities of cutting-edge technologies like machine learning and AI, cloud-based computing can help farmers improve crop yield, health, quality, and overall outcomes by leveraging the power of big data in agriculture.

Here are 3 specific examples of how cloud-based solutions benefit agriculture: 

  1. Increased efficiency in team collaboration – Cloud-based applications provide a centralized platform for multiple individuals from different organizations to work together seamlessly, regardless of technical aptitudes. This results in more effective collaboration and faster decision-making.
  2. Improved data-driven decision-making – The ability to access real-time data enables farmers and agronomists to make changes to their practices in a timely manner. For instance, the use of drone data can provide an accurate assessment of the health of crops, while soil moisture probes help to adjust irrigation practices in real time, leading to better yields.
  3. Streamlined project management – By connecting growers, field trial managers, and agronomists in real-time, cloud-based applications provide a centralized Ag-focused platform for on-farm experiments, allowing for better project management and increased impact. Additionally, the use of cloud-based systems helps to reduce the amount of manual data entry, making it easier to transcribe and use data to its full potential.

Additionally, with a cloud-based Ag solution, there is:

  • No installation needed
  • Quick onboarding
  • Maximized scalability
  • Simple configuration

It is critical to understand that with an on-prem Ag solution, the number of users dilutes the performance ability, thereby affecting usability and achieving results.

Agmatix’s Next-Generation of Cloud-Based Solutions for Agriculture 

At Agmatix, we believe in creating a world where high-quality and standardized agronomic data is available, enabling Ag professionals to break data silos, overcome obstacles and improve sustainable food production and quality. 

With our mission to harmonize and standardize all agronomic data and make it universally accessible, we strive to change the world with the best data-driven solutions. Our platform is rooted in our values of being data-driven, daring, determined, trustworthy, and always improving. Join us as we explore the future of agriculture and the role of agro informatics in shaping a better world. Read on to learn about our key Ag offerings.

Digital Crop Advisor

The Digital Crop Advisor is a unique and innovative tool designed to help agronomists and agriculture professionals optimize crop nutrition management at scale. It combines state-of-the-art technology, data insights about the local environment, and expert knowledge to make science-based crop nutrition decisions to help increase yields and lower the environmental footprint. 

The solution provides ag-input sales agronomists instant access to all product listings and enables field agronomists to create tailored crop nutrition management plans that deliver results sustainably. For food producers, it allows for the implementation of field-level protocols based on R&D efforts that increase yields, quality, and profitability.

The solution also provides a full picture of your crop production with deep insights into carbon emissions, project management, and collaboration capabilities, allowing users to view the real-time status and fluctuations of all operations worldwide and filter by location and date to easily find what they need. It also provides a digital touch point with growers for real-time recommendations.

Field agronomists can provide growers with a deeper understanding of the impact that individual nutrient plans have on their crops and the associated carbon emissions. They can offer real-time recommendations based on data-driven insights. 

The solution is equipped with 12 scientifically-proven crop nutrient data profiles, enabling efficient crop nutrition optimization and easy analysis and reporting. The software also allows for a paperless environment and helps maximize ROI. 

The solution provides sustainable nutrient recommendations per each plan created, based upon the unique carbon footprint analysis of that plan, which enables users to quantify and compare sustainability KPIs. The algorithm correctly adjusts crop nutritional needs and helps understand the tradeoff between maximizing yields and minimizing detrimental environmental effects.

Agronomic Trial Management

The Agronomic Field Trial solution is a cutting-edge solution for managing all aspects of your agricultural field trials. The precision farming tool offers a range of capabilities made possible by its cloud-based design which provides a complete end-to-end unified platform that includes planning, analysis, mobile data collection, and reporting. and project management as well as collaboration.

The platform’s reporting capabilities provide complete insight into your trial’s progress, allowing you to manage budgets, monitor protocols vs development, and analyze all factors that affect trial performance. Researchers may quickly connect with trial operators, field technicians, and CROs using its user-friendly interface, ensuring everyone is on the same page.

The platform’s mobile data collection feature allows you to collect data and observations from your mobile device, whether you are in the field or at your desk. You can receive insights on the performance of your trials, helping you make informed decisions about product performance and marketability. 

Finally, the platform’s project management and collaboration capabilities allow you to share data with staff members and partners outside your organization, improving collaboration and decision-making across your entire team, all within a unified platform

Axiom Technology

Axion technology is the key to unlocking a huge potential from agronomic data. Within this technology engine, data is ingested, validated, enriched, and leveraged by in-house ontologies with various sources to standardize, harmonize and enable agronomic predictive modeling, research, and field trials. 

AI-driven insights are another key capability that Axiom provides the solutions within the Agmatix platform. With advanced machine learning algorithms, the platform can analyze the data and provide recommendations within the solution to users.

Axiom also enables better collaboration capabilities because it standardizes agronomic data and houses it in a unified cloud-based platform for Agmatix’s customers. This means multiple ag professionals can access, share and work within the same data sets, to gain better insights with the assurance that all data is comparing apples to apples. This helps Agmatix customers increase their productivity and efficiency.

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Cloud-Based is the Foundation for Next-Gen Ag

The growth of agtech applications in agriculture through cloud computing will drive significant change for environmental protection and food security. The wider the adoption, the greater the positive impact will be, with accessibility playing a critical role. Agmatix is leading the charge towards the next stage of agricultural advancement, creating cutting-edge, cloud-based solutions.

Building a Forest of Communicators for Ecological Stability in Agriculture

Communication: how often do you think about the role it plays for us? 

Humanity and modernization owe a huge debt of gratitude for communication. It was one of the most significant developments in the history of mankind. Communication is a set of rules that enables information to be exchanged using a symbols system that follows a structure of relations. 

In fact, the ability to communicate creates a stable biological ecosystem – ecological stability. 

Plants also communicate in different ways. One of the famous examples is in a forest, where two species of trees can communicate through the underground fungus mycelium – a third species. They can transfer food, water, and information on what is happening in the forest today. In some ways, it’s the equivalent of two neighbors gossiping! 

By communicating, they allow biological stability for the forest ecosystem. Strong high trees support smaller ones in their development when the light of the forest ground is limited due to high tree population. They do so knowing that one day the favor will be returned, transferring food or sharing information on pests, allowing them to synthesize the antigen before pest appearance. 

The largest fungus in the world is called the Humongous Fungus, is estimated to be 2000 years old. It’s spread over 10 square kilometers in Oregon’s Blue Mountains! Only imagine the amount of data it transforms over the years. Think about the age of this forest. It has survived – and thrived – for millions of years because of ecological stability, enabled by communication between organisms in the forest. 

Ecological Stability and Agriculture

Ecological Stability refers to the ability to return an ecosystem to its equilibrium state after a perturbation. This is known as resilience. A hallmark of Ecological Stability is the ecosystem not experiencing unexpected large changes in its characteristics across time. 

In the agricultural ecosystem, there are several symptoms of low stability. These include soil erosion, soil health degradation, increasing concentrations of contaminants, and more. These signs are generally connected to human activity. 

Soil erosion is the result of extended machinery usage, such as deep and frequent tillage, or removal of the natural canopy cover. Exposed soil then erodes away and can become a pollutant. 

Soil health degrades because of reductions in biological activity, nutrient deficiency, or changes in soil physical properties. A host of agricultural practices create an environment where these things occur. 

Contaminants occur in increasingly high concentrations because of chemical use and unbalanced usage of recycled organic materials.  

The ability to mitigate those changes requires a deep understanding of complex systems that includes a large number of parameters. These parameters are interconnected, affecting each other in changing environmental conditions. Addressing just one parameter will not address the Ecological Stability challenge. 

Science and Data for Ecological Stability

Solving these problems will require a holistic approach. Investigating nature requires the ability to compare the environments with the change of only a few single variables.

This is how an experiment is conducted. A field trial is the best way to collect the agronomic data that will become the basis of further research. Many trials or datasets describing the agricultural reality can help reveal mechanization and the relation of the parameters affecting Ecological Stability.

But, experiments today conducted by one group are often not shared with other groups. The amount of data labeling and number of protocols is enormous. In general, the agricultural society lacks standard methods to support agricultural data sharing. Therefore the experiment’s agronomic data stays siloed, undermining the ability to solve complex problems.

Communication in Agricultural Data Systems

This brings us back to communication. To effectively address the multifaceted issues within agriculture, it is imperative that we establish a robust system of communication. This involves creating a framework of rules and relationships that enables researchers to access and analyze comprehensive agronomic data sets, which can provide a more complete understanding of the complexity of agricultural challenges. By fostering an environment that encourages collaboration and the sharing of information, we can enhance our ability to address the diverse challenges faced by the industry and develop effective solutions that benefit all stakeholders.

For example, if we wish to reduce soil erosion while maintaining high yields to support humanity, we must investigate the practices that reduce tillage and increase cover cropping. At the same time, we have to take into consideration the crop genetic properties, sensitivity to soil disease, and the plant nutrition and irrigation needs in this system – including those needs specific to cover crops.

Or, if we all wish to reduce the chemicals used in agricultural fields, we should find solutions related to plant protection in agricultural practices, such as net houses or biological species that eliminate pests. Again, we will need to learn how these affect water nutrition consumption and what genetics can best deal with this practice. 

The interconnected agriculture systems mean data collection and sharing is even more important for fully understanding downstream impacts and holistically addressing Ecosystem Stability challenges. Connectivity – and the data collection and analysis that stems from it – is predicted to add value to the global GDP of up to $500 billion by 2030. 

Agmatix and Agricultural Data Sharing

Agmatix, an agronomy data science company, understands the importance of interconnectivity and communication in agriculture. That’s why we’re focused on creating solutions that work behind the scenes – or underground, like the fungus in the forest, to standardize, harmonize, and make data available for the betterment of the agricultural industry. 

Axiom technology enables agricultural data standardization and harmonization so different datasets – like different tree species – can communicate. Axiom uses in-house ontologies with multiple sources to create a common language, or common protocols, for datasets created using different methodologies and protocols. Agricultural data ingestion, integration, and standardization turn big agricultural data into powerful, actionable insights to support Ecological Stability. 

Through Axiom technology, it’s possible to leverage multiple datasets in a single analysis. But accessing quality agronomic data can be a challenge, too. 

Through collaboration across the industry, Agmatix is opening doors for open-source agriculture databases. These databases are designed to spur innovation and support ongoing research. Alongside the International Fertilizer Association, Innovative Solutions for Decision Agriculture, African Plant Nutrition Institute, and Wageningen University & Research, Agmatix has led the creation of two databases: the Global Crop Nutrient Removal Database and the Nutrient Omission Trial Database.

The Global Crop Nutrient Removal Database helps assess the impact of production and environmental variables on nutrient concentrations to help calculate the total nutrients extracted from the field during harvesting. This open-source agronomic database provides data that links crop nutrient inputs and outputs across diverse production settings. Through this dataset, crop nutrition practices and management can be refined to enhance sustainability and improve crop yields. 

The aim of the Nutrient Omission Trial Database provides data to support optimized nutrient management and aid in site-specific recommendations. This data allows researchers to compare crop nutrient requirements and create tailored plans that account for variations in soil fertility and other environmental factors. 

To create a standardized and open data set, the GUARDS protocol was used to consolidate nutrient omission research data from multiple sources. This simplifies the integration of the data into advanced fertilization tools and fosters better collaboration among members of the Consortium for Precision Crop Nutrition.

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Data Science to Support Ecological Stability for the Future

We, like the fungus in the forest, must transfer knowledge between the different ag professionals in the various domains just like different tree species must communicate in the forest to survive and maintain Ecological Stability. If we wish to build a resilient world where agriculture and nature live in coexistence, we must rely on communication to build deep understandings of ecosystems that form the basis of future innovations for sustainable agriculture. 

This post was written by Dr. Sagi Katz. Dr. Katz has been involved in agriculture since a very young age. He holds a Ph.D. in Soil and Water Science specializing in the ecosystem of the usage of treated wastewater in agriculture. He has been working in the agri-tech ecosystem area for several years and has acquired vast knowledge and experience in the field. Dr. Katz currently serves as VP of Agronomy at Agmatix. He is also responsible for the company’s Ontology engine.

Data Analytics at the Center of Next-Generation Agriculture

Every aspect of agricultural processes can be captured into a data point. From factors like soil temperature and moisture at planting to variable rates of nutrients applied to pest and disease pressure, key data can be captured throughout the growing season. At harvest and beyond, yield and quality data, climate data, and marketing data can all shed light on the crop and business. 

That data becomes meaningful and impactful for future agricultural decisions through its applications in data analytics. When data is transformed into insights that can be used to better understand agronomic, economic, and environmental conditions, users can drive innovation and improve agriculture’s sustainability every season. 

Big data analytics and digital transformation are the essential bridge between agriculture today and new-generation agriculture. Agriculture data analytics companies like Agmatix are leading the way in creating tools to enable new-generation capabilities.

How Is Data Analytics Used in Agriculture?

Data analytics is critical for agriculture. In modern agriculture, as more data is collected and stored automatically, the opportunity for data to make an impact is massively increasing. Both qualitative and quantitative data are collected on farms and in agriculture. 

For example, yield data is qualitative data that provides a report card on crop productivity and is often used to make decisions about crop varieties for the following year. Drone imagery of a growing crop provides a quantitative dataset that can be used to make decisions about nutrient or fungicide applications. 

All four categories of data analytics – descriptive, diagnostic, predictive, and prescriptive –  have the opportunity to inform innovation in agriculture. From describing the impact of a weather event on a crop to predicting yield outcomes relative to a new production practice, agricultural data analysis can shed light. Diagnostic analytics can precisely point to possible reasons for a specific response in a crop, and clarity about how to adjust nutrient application rates for a specific soil type comes from prescriptive data analytics. These four categories are commonly used in precision agriculture applications

A variety of sectors within the industry rely on agricultural data analysis. Crop yields, specifically, can be improved through data analytics for precision agriculture. Maximizing active crop time through strategic crop rotation can maximize yields. Determining this manually would be challenging; but through data analytics, machine learning can analyze datasets including weather patterns, soil types, temperature readings, and satellite imagery to pinpoint the crops best suited to that environment. 

Resource allocation on the farm can be a very challenging balance between maximizing profitability, environmental sustainability, and crop productivity. Water, nutrients, and pesticides are all critical inputs that are consumed during the growing season. Using machine learning to analyze soil conditions – like nutrient and water levels – can help farmers make irrigation and fertilizer adjustment decisions in real-time to ensure plants have what they need to maximize production without wasting valuable inputs.

Lastly, farmers are impacted by a changing climate. Adjusting to these changes means historical knowledge and tried-and-true schedules are no longer accurate. Weather patterns can change from year to year, making planting and harvesting timeline decisions difficult. 

Analytics models can compare historical weather trends with recent weather trends to predict upcoming conditions. Armed with this information, farmers can adjust planting schedules and harvesting timelines. 

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How Is Agmatix Contributing to Next-Generation Agriculture?

Agmatix is harnessing agriculture data science to drive innovative technologies that move agriculture towards a more sustainable and productive future. It’s an agriculture data analytics company focused on creating a world where high-quality, standardized agronomic data is put to use to tackle the toughest challenges facing agriculture. That work has already taken the shape of several different Agmatix platforms that utilize agriculture big data analytics

Digital Crop Advisor is designed to provide optimized, data-driven nutrition plans to optimize crop yield and environmental sustainability. Agronomists can run simulations and allow the algorithm to adjust for crop nutritional needs. This enables users to compare multiple recommendations for key outcomes, including understanding tradeoffs between yield and environmental impacts. 

The Agronomic Trial Manager unlocks next-generation field trials. Through an intuitive, cloud-based system, end-to-end management of field trials is easy. Collaboration and reporting are straightforward, supporting fast decision-making and speed to market. 

Insights and models, supported by agriculture data analytics, reveal new value from data. Through analyzing aggregated and standardized data, such as field trial results or legacy trial data, the Agmatix platform can convert it into agronomic insights and crop models. This approach will take agronomic data further than it’s ever been. 

Agmatix values open data and powers open databases in collaboration with the International Fertilizer Association, Wageningen University & Research, the African Plant Nutrition Institute, and Innovative Solutions for Decision Agriculture. 

The Global Crop Nutrient Removal Database is designed to create a holistic database highlighting the relationships between nutrient inputs and outputs in a variety of production and environmental conditions. Through understanding crop nutrient removal, agronomists can adjust for specific nutrient amounts required for the next crop on that land. 

The Nutrient Omission Database is intended to provide data that leads to site-specific recommendations and optimized nutrient management. Legacy nutrients that have accumulated in the soil over multiple years of fertilization can contribute to crop nutrition; having data around these levels allows this information to be an input into advanced fertilization tools and nutrient management plans. 

There is a myriad of ways that Agmatix is harnessing the power of data analytics to transform agriculture. The next generation of agriculture will be powered by data analytics that predicts, diagnoses, describes and prescribes actions and results that ultimately make each season better than the next. The impact of next-generation agriculture will be immense as the industry grapples with feeding a growing population and caring for the environment. Agmatix will be leading the way with data analytics for precision agriculture and a better world. 

Knowledge Is Power, Use Data To Fuel Better Decisions

Decision-making is part of everyday life for all of us. In fact, humans make an estimated 35,000 decisions a day. From what to wear to which route to take to which strategy to adopt, humans make decisions all the time. Some of those decisions might be made impulsively, through carefully balancing alternatives, by prioritizing, or even by pushing the decision off to others. 

If you are a farmer, everyday decisions and how you make them can have a big impact – on your business, on the environment, and on worldwide food scarcity. Agronomists, agriculture professionals, researchers, and policymakers have the same vast impact derived from their decisions. Those decisions will become even more important as the agriculture industry continues to face challenges like climate change and a growing population.  

As the world population approaches 10 billion by the end of this century, producing enough high-quality food to feed every hungry mouth will be paramount. And while the population will increase, the availability of arable land and other natural resources will not increase. Ultimately, this demands efficient use and protection of existing resources to maintain their viability well into the future. 

This means the impact of farmers’, agronomists’, researchers’, and other industry stakeholders’ decisions will be magnified. From determining the best crop rotation strategy to creating nutrient management plans to deciding whether to apply fungicide, farmers’ decisions will directly tie to their own profitability and viability as well as the sustainability of the world’s population. 

Decision-making in agriculture can be supported by the vast amounts of agronomic data collected in modern agriculture. Data science and data analysis provide information and insight that support balanced decisions. With advancements in agriculture data systems, it’s easier than ever for data to be a key support in making sustainable decisions. 

Types of Data in Agriculture 

Agriculture data science has evolved alongside the agriculture industry. Technology has enabled agriculture to grow in scale and precision; no longer are many tasks on the farm done by hand or row by row. Mechanization and automation have also created opportunities for additional data collection on the farm that add to the traditional methods of collecting data for decision analysis. Now, there are several types of data collected and used in agriculture. 

  • Non-tangible data: for centuries, people have used gut feelings and advice from more experienced people to inform decisions. Farmers are no different – and in some cases, farmers may have even used printed prediction materials like the Farmer’s Almanac to make decisions. These inputs to decision-making aren’t datasets that are scientifically collected or statistically significant, though they may still have value to a given farmer. 
  • Manually collected data: farmers have long been manual collectors of data. A peek inside a tractor or truck cab used to frequently reveal a stained notebook or two detailing weather patterns, pest pressure, or even charts of crop varieties by field. 

Some of this data is now collected automatically, though many farmers still manually collect weather data or crop scouting records. Today, many do so in mobile apps instead of with paper and pen. This is a valuable set of observations that works well in combination with automatically collected data. 

  • Automatically collected data: connected equipment can capture real-time, precise, and location-specific data. Drones and sensors on equipment – like irrigation infrastructure or row crop farm machinery – automatically gather data. In many cases, this data can be shared automatically with cloud-based systems to enable real-time adjustments. 
  • Shared data: open source databases or collaborative information shared between professionals is data that can enrich localized datasets. Agronomic databases like the Global Crop Nutrient Removal Database provide global, open, comprehensive information to support decision-making. This type of data promotes open science and collaboration, enabling the world’s best minds to work together to solve agronomic problems. 

Together, these agriculture data systems provide a complete picture of an acre, a field, a farm, or a production system. This collective viewpoint supports informed decision-making.  

Next-Gen Agriculture Begins With Data-Driven Decisions 

In today’s agriculture industry, critical decisions can be supported by accurate, real-time data. Many different stakeholders in the industry benefit from data supporting their decisions, including farmers themselves, agronomists, researchers, agriculture companies, and even policymakers. 


For farmers, data can support many decisions. Agronomic data science can inform decisions around varieties, crop rotations, application timing, and more. Smart crop monitoring, like drone-based imagery, can provide insight into remote corners of fields that are difficult to reach and understand. Monitoring crops for quality characteristics like moisture, or fruit color can help farmers harvest at precisely the right time to maximize crop quality. Data can even reduce the number of decisions that farmers have to make through data-driven automation and autonomy. 

Small-scale farmers and growers have much to gain from data-supported decisions. In one study, data-supported machine learning algorithms used in management practice guidelines on small-scale farms in Colombia led to high yields with less failure risk. McKinsey notes that the value of connectivity is higher in Latin America, Asia, and Africa, where yields are not yet optimized.


For the trusted advisors that help farmers optimize crop nutrition and manage pest and disease pressure, data is a critical input to decision-making. Access to near real-time data from a variety of sources – such as soil moisture sensors and nutrient sensors – can enable the swift creation of prescriptions to address nutrient deficiencies or pest pressure. 

The combination of the agronomists’ background, education, and localized knowledge with available datasets allow fast decision-making that protects yield potential. Agronomic data science plus a deep knowledge of fertilizer and crop-protectant technologies will help agronomists deliver unique perspectives and solutions to growers. 

Researchers and commercial companies 

For scientists, developers, researchers, and marketers, ever-increasing datasets allow enhanced collaboration, customer value, and innovation. The world’s best minds working together unlock maximum value from the data. This collaboration is key to overcoming obstacles on the path to innovation. 

Data can also support decisions end-use consumers make in regard to which companies’ products they want to buy. This is a key marketing tool for agricultural companies that want to address consumers’ desires to understand where their food comes from. Data is the foundation of food traceability

Data also supports researchers and companies in accelerating innovations through product pipelines. Time to market can be reduced through data collection on testing at scale. And decisions about product readiness and efficacy – as well as marketable claims – can be made confidently when supported by data. 


Data systems are critical for the development of agricultural policies and programs. Data-based models can be used for agricultural policy analysis and economic impact assessments. As policymakers create frameworks that drive sustainable natural resource management, data can help model on-farm decision-making and impacts on the natural environment. 

Data Alone Doesn’t Make Decisions 

Alone and without analysis, data is an ineffective catalyst for change. But when people are armed with data and the tools to use it, it can become an incredible basis for making crucial decisions. 

Agmatix, a global agro informatics company, creates tools that unlock agriculture data insights to empower field-level decisions. Agmatix’s suite of tools enables agriculture’s biggest stakeholders to communicate freely with the intent to solve agriculture’s biggest challenges. 

This starts with Axiom technology standardizing data into a single standard language with rules, ontologies, and taxonomy. When data is apples-to-apples, regardless of source, it can be used to provide context and perspective to support informed decisions. 

The Agronomic Trial Management solution supports the collection of critical data throughout the growing season. This system has end-to-end capabilities for planning, executing, and analyzing results from agronomic field trials. Ultimately, this connects trial coordinators, field technicians, and research scientists to real-time data throughout the field trial. This real-time data is a key input for real-time decision-making. Armed with this information, data can help support new innovations as they are assessed for efficacy, safety, and market potential. 

Digital Crop Advisor is a data-based decision support system designed to provide options to support agronomists in making the best recommendations in the context of real-world situations. Digital Crop Advisor creates crop nutrition plan options for up to 12 nutrients and over 150 crops; this provides flexibility for agronomists to combine the data-based options with their localized knowledge. Digital Crop Advisor also allows users to compare nutrition plan options and understand tradeoffs between sustainability and yield potential. 

Agmatix is committed to open-source data and believes in the value of collaboration for driving innovation. The Global Crop Nutrient Removal Database is one example of this. It was created in collaboration with the International Fertilizer Association, Innovative Solutions for Decision Agriculture, the African Plant Nutrition Institute, and Wageningen University & Research. It aims to support collaborative decision-making around crop nutrient needs to optimize for sustainability and crop productivity. 

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The Importance of Data Standardization and Harmonization to Innovation

Data Supporting Decisions 

Agriculture is faced with many challenges, and the scale of those challenges will only increase with time. The decisions made by farmers, agronomists, researchers, and companies in agriculture add up to a big impact over time. 

That’s why it’s so important to leverage the available data and data tools to inform critical decisions. Agmatix is committed to supporting agriculture’s decision-makers with the tools and open data needed to confidently make decisions that balance both sustainability and crop productivity. 

When good quality data is placed in the hands of agriculture experts, decision-making isn’t driven by the data, it is supported by the data, leading to the most educated and effective decisions possible. 

The Importance of Data Standardization and Harmonization to Innovation

Data has an ever-increasing role in agriculture. From input decisions to changes in production practices to increasing levels of automation, data is powering progress for farmers. Data is also being collected in many different ways around the farm. With cameras and sensors along for the ride on many passes through the field, farmers have a whole new view of their land and crop performance. 

As data shows so much promise on the farm, it’s no wonder why bringing it back to the basics of data management is so important. Ensuring that data has a solid foundation – built on data standardization and harmonization – protects the integrity of the dataset and increases effectiveness when the data is put to use. 

What is data standardization?

Data standardization is the process of converting data into a standard format and utilizing that across the board. One agronomy data standardization example would be making all plant measurements using the metric system. More generally, data standardization can be as simple as listing all dates in a dataset as YYYY-MM-DD. 

Data standardization ensures all people recording data for experiments are measuring and entering data in the same way. Typically, this is determined prior to an experiment in a standard operating procedure (SOP). This keeps the data collection team aligned and minimizes data cleanup after data collection is complete. 

The purpose of data standardization is to improve data quality and usability, reduce errors, and improve communication and collaboration across teams. Overall, this strategy results in improved decision-making generally and in agronomy applications. 

Why is data standardization important?

Data standardization plays an important role in ensuring data-based agronomy decisions are effective. In fact, data standardization can be the bedrock for the critical collaboration that occurs between growers, farmers, agronomists, and industry researchers. The benefits unfold in a few different areas: 

  • Upgrading data quality and usability: with fewer errors in data entry, data quality, and usability are simultaneously improved. This is a big net positive!
  • Enhancing communication and collaboration: having standardized data actually makes the data more shareable across team members. It ensures everyone is speaking the same language. This improved transparency allows for more collaboration and communication within and across teams. 
  • Improving decision-making: clean and consistent data enables researchers to focus on the important questions and tasks at hand, rather than worrying about whether data is formatted correctly or entered incorrectly. Standardized data is immediately available for analysis and collaboration. This increases efficiency and speeds up the process of finding the answer or making the final decision.  Agronomists, researchers, and farmers can move quickly towards necessary changes or adjustments. Making fast decisions and learning quickly enables innovation at a faster pace. 

What is data harmonization?

Picture a symphony hall with music swelling to the rafters. That music is only a beautiful sound if everyone is in harmony! When different notes, heard simultaneously, come together in a single composition, that’s harmony – and it’s a sweet sound. 

Data harmonization is similar to musical harmony. It’s the act of unifying data from several formats or sources into a single location. This combination of data from different sources provides people with a view of data from different sources represented in a similar way.  When all the data comes together to form the big picture, you can get a totally different view.

A general example of data harmonization would be bringing together multiple years of a similar study on a single topic. Agronomically speaking, data harmonization might mean bringing together data collected in separate passes across the field, or ingesting data from a worldwide database to complement local data collected in an on-farm experiment. 

Data harmonization and standardization work together to ensure data is apples to apples – or all speaking the same language – and ready for analysis. They improve data quality and reduce redundancy, making data transfer and collaboration easy. 

Even though it’s critically important, standardizing and harmonizing data isn’t always easy. Legacy data, multiple data sources, and large raw datasets can make this process complex. 

What is Agmatix’s role in data standardization and harmonization?

Agmatix, a global informatics company, is dedicated to growing data for impact through innovative platforms that empower field-level decisions. A big part of enabling agronomic insights is agricultural data harmonization. Agmatix’s Axiom technology includes an agronomic data harmonization platform that ingests and integrates data for predictive modeling, agronomic research, and field trials.

Axiom technology is used by in-house ontologies with several sources to standardize and harmonize data. This powers big data’s transformation into powerful insights. Agronomic analysis software speeds the time to insights from this data through powerful insights and models that can even leverage legacy data. The cross-trial analysis becomes possible, providing an additional perspective. 

The GUARDS (Growing Universal Agronomic Data Standard) protocol enables agronomic data standardization. It’s intended to translate data – regardless of the unique way a researcher preserved it – into a single common language. This translation process means that any researcher in the world can use that data – and it’s based on the FAIR data principles. 

The GUARDS protocol system actively monitors data integrity and quality using ML. This proactive approach then alerts for abnormalities in datasets when needed. The unit converter translates measurements into a standardized unit. Through this process, databases and values can be customized. 

Standardized and harmonized data fuels decision-making in many areas of agriculture. Having the right tools to support these decisions can be critical. Agmatix has platforms that can take data from standardization and harmonization all the way to action through the Digital Crop Advisor crop nutrition recommendation tool. Once data is standardized, it can be ingested in a unified, cloud-based system to share and collaborate within a single organization or with external collaborators. Having a unified platform enables seamless data sharing and collaboration. This is one example of Agmatix and data together fueling action that makes a real difference for farmers and the environment. 

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Data’s foundation for evolution

No matter how much, or how little, data you work with, data standardization and harmonization are extremely important. Transparent, high-quality data ensures that data-driven decisions will make each season better than the last. These data-driven decisions can help overcome some of agriculture’s biggest challenges – and make a meaningful difference in supplying a growing world with healthy, accessible, and sustainable fuel. 

At Agmatix, our mission is to power agronomy data standardization and harmonization to turn it into actionable insights. We want to make this process seamless so you can focus on what’s important – making efficient and informed decisions. Let us help you! 

Data Science Powers Innovation

The Disruptive Nature of Data Analytics

Disruptive innovation in an industry – where a company with fewer resources takes on established businesses – has the potential to change the landscape and bring new opportunities forward.

Data science presents context and insights to drive disruptive innovation. In the medical industry, understanding data around percentages of medical conditions treated in medical clinics led to the disruptive rise of retail medical clinics to address low-end market needs. Similar opportunities for low-end disruption and new market disruption exist in spades in agriculture, too!

Data science is a space where various scientific, technological, and socioeconomic factors interconnect. These factors can include data and data source availability, high performance analytical processing, open-source analytics, applications that are business and market-ready, and societal global challenge focus. Data science can also be described as the space where analytics, statistical modeling, data mining, artificial intelligence, and monitoring systems intersect. 

Data science isn’t a new concept. It’s been around since the 1960s when a mathematician predicted an empirical science would be born from modern-day electronic computing. Once the personal computer hit the market and households around the world, data science began to take shape, though data was mostly just collected without conversion into insights. Rapid growth in the data science space occurred in the early 2000s with the rise of AI, deep learning, and machine learning applications. 

This 50-year evolution has led to changes in almost every industry worldwide. From personalized healthcare recommendations to route-optimization models that minimize traffic and optimize shipping routes to digital ad targeting, data has created opportunities to see things differently. This has also resulted in innovation in agriculture. 

Innovation in Agriculture

Innovation in agriculture through data science opens the door for new products, services, technology, and even business models. Innovation can take shape in two different ways: identifying an improved solution to address an existing problem, or redefining a known existing problem to make it more meaningful, and then finding a method to solve it. Both types of innovation are powerful, though usually start from different places. 

Innovation around a known problem usually mandates strong expertise and a focused view of an area. Reframing an existing problem requires a holistic view of related spaces to the known challenge. Opportunities for both innovation types exist in agriculture. 

Agriculture has always been an innovative industry. From solving the problems of sticky, midwestern soil with the self-scouring plow to a unique barbed wire that finally found a way to keep cattle contained, agriculturalists have been known to think outside the box to solve well-known problems in new ways. 

In recent years, agriculture innovation has been fueled by data science. For example, GPS system integration into farm machinery has made tillage, planting, spraying, and harvesting more accurate. This technology has taken over the industry, saving inputs by reducing pass-to-pass overlap and allowing effective, environmentally-friendly production practices that require precision – like strip-till or side dressing – to take hold in mainstream row-crop agriculture. 

When farmers have data-based prescriptions for seeding population or nutrient applications and GPS systems that place machinery in just the right place, it’s possible to adjust input rates at a sub-field level. This reduces inputs overall and increases their effectiveness. 

Satellite imagery is another example of innovation in agriculture. Field characteristics can be understood from satellite images, and fields can be broken into unique management zones for more precise management. Seeding population and nutrient application strategies can be set for sub-field areas defined by satellite image views of the bare soil. This increased precision through data science helps farmers to understand their land and adjust management to only use what inputs are truly needed – a win-win for the business and the environment.  

Farmers and agronomists have even taken to the skies with innovation in agriculture. Drones have become another tool for monitoring crop health and disease pressure across many acres. Data collected from drones can be used to make decisions on fungicide or nutrient applications for growing crops to maximize yield and profit. This new view and new data help farmers to make decisions with important economic and environmental sustainability impact. 

These innovations are just the start of using data science in agriculture for increased productivity and sustainability. Artificial intelligence, machine learning, and deep learning are all part of the technology suite that’s driving agriculture forward. 

This aligns with Food and Agriculture Organization’s efforts to increase farming sustainability. Their 2030 Agenda for Sustainable Development calls for enhanced cooperation and knowledge sharing to improve access to technology and innovation. Ultimately, this supports the objective of ending poverty and building economic growth while responding to climate change. 

Specifically for agriculture, protecting the environment and natural resources is key. The FAO is focused on innovation with a systems approach and addressing smallholder farmer needs. Scaling innovation in agriculture requires coordination across the industry, sectors, and partners, including both public and private sector stakeholders. 

Agmatix Fuels Data Science and Agriculture Innovation

Agmatix, a global agro informatics company, is creating a world where high-quality and standardized agronomic data is freely available. This supports ag professionals globally to overcome obstacles in improving sustainable food production and quality in alignment with the FAO Agenda for Sustainable Development. 

Agmatix’s work is data-driven and cutting-edge. We have a constant state of mind to improve, grow, and learn. We strive to change the world for the better with the best solutions for agriculture. That starts with open-source, high-quality, standardized data.

Agmatix’s data science and agriculture innovations include Axiom technology, Agricultural Trial Management, and the Digital Crop Advisor solutions. These data-driven tools unlock impactful insights to empower decisions on the farm. 

Axiom is a disruptive technology that standardizes and harmonizes data from various sources. The GUARDS (Growing Universal Agronomic Data Standard) protocol is based on the FAIR data principles with a specific focus on data interoperability and reusability. This includes standardized definitions with a unique bottom-up approach, leveraging ML capabilities, and unit conversion. Automatic agricultural data ingestion allows Axiom to digest data at scale, even from multiple sources, with a low cycle time and high integrity. 

Agricultural Trial Management is designed to improve productivity and efficiency while increasing the quality of field trial data. End-to-end capabilities give visibility and control throughout the entire field trial. The mobile application enables seamless in field data collection and management for instant data validation and analysis. Collaboration across all stakeholders – from trial operators and researchers to farmers – is easy, especially with field trial data that’s easily accessed, shared, and understood. Quick, data-driven decisions are possible when field trials and field trial data is well-managed. 

Digital Crop Advisor is an agriculture data science application that optimizes crop production and creates nutrient prescription plans in an easy-to-use dashboard. Big data insights help quantify and compare sustainability KPIs such as carbon footprint and nitrogen leaching. It’s even possible to compare tradeoffs between productivity and environmental impact to make educated decisions about crop nutrition. This innovative tool supports agronomy teams in addressing sustainable agriculture at any scale. 

Agmatix’s data science-based solutions support agronomists, researchers, companies, and farmers in making a difference in agriculture and in the world. Supported by open source, high-quality data, Agmatix is determined to support sustainability. 

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Moving Forward 

Data science will prove to be a key part of innovation related to the future of agriculture. When it comes to food production and sustainability, data science will fuel new approaches to balancing productivity and environmental friendliness. Some of that innovation is taking place now – and Agmatix is one example of how data science applications in agriculture illuminate a better future. 

Agmatix works to leverage past and current data to help you make the best decisions  – whether that’s tackling a known problem in a new way or redefining a problem to make it more meaningful when solved. Opportunity will be unlocked through data science in agriculture. Take the next step in your innovation with Agmatix. 

The importance of digital tools in modern agriculture to successfully implement the 4R approach

Agriculture has a huge job: providing the food, fuel, and fiber needed to sustain the world’s population. Few industries have such a tremendous influence on the day-to-day lives of every person. Today, that means feeding just over 8 billion people. By 2050, farmers around the world will be feeding nearly 10 billion people while managing limited arable land and declining natural resource availability.  

In order to achieve this, minimizing environmental impacts from agriculture is critical. Increasing the productivity of agricultural land will also be required. These two concepts don’t always go hand-in-hand; but through proper management and agriculture technologies, it will be possible for farmers to both care for the Earth through sustainable production and increase production to meet growing demand. 

One clear way to achieve optimal crop production while simultaneously minimizing environmental impact is through the 4R nutrient management strategy

4R Nutrient Strategy 

The 4R nutrient strategy, which stands for the right source, right rate, right time, and right place, is a framework for optimizing the use of fertilizers in modern agriculture. The 4R approach aims to maximize the efficiency of fertilizers by ensuring that the right type of fertilizer is applied at the right rate, at the right time, and in the right place. Oftentimes, these factors are interconnected and may need to be addressed together. 

Right Source

The right source of fertilizers means selecting the appropriate type of fertilizer for the specific needs of the crops being grown. Considerations may include: 

  • Nutrient composition of the soil
  • Specific nutrient requirements of the crops
  • Fertilizer nutrient availability for delayed or immediate uptake
  • Combinations of fertilizers 
  • Economic and environmental constraints 

For example, a field with high levels of phosphorus may not need additional phosphorus. A legume crop that biologically fixes nitrogen may need less supplemental nitrogen throughout the growing season.

Right Rate

The right rate of fertilizers refers to applying the appropriate amount of fertilizers based on the needs of the crops and the characteristics of the soil. Considering the right rate means thinking through: 

  • Crop nutrient demand
  • Soil nutrient analysis 
  • Application equipment capabilities and precision 
  • Crop yield goals 

This is important because: 

  • The inappropriate application of fertilizers can result in nutrient runoff and pollution
  • Under-applying fertilizers can lead to reduced crop yields
  • Carefully following recommended application rates for fertilizers ensures that they are being used efficiently and effectively

Right Time

The right time to apply fertilizers is also critical. Application at the wrong time can result in nutrient losses or reduced crop yields. The right time means understanding:

  • Soil structure and ability to retain nutrients 
  • The possibility for climate-driven nutrient loss
  • Crop type and nutrient needs throughout the growth cycle 

The right timing strikes the balance of best nutrient uptake and minimal nutrient loss. For example, applying fertilizers when the soil is too dry can cause them to be ineffective. On the flip side, applying fertilizers when the soil is too wet can result in nutrient runoff. 

Right Place

The right place means considering the appropriate location for applying fertilizers based on the needs of the crops and the characteristics of the soil. This may include: 

  • Applying fertilizers directly to the root zone of the crops
  • Incorporating nutrients into the soil through tillage or other means

The appropriate placement will differ based on crop type, growth stage, and growth rate. It’s important to carefully consider the location of fertilizer application to ensure that the nutrients are being delivered to the areas where they will be most effective.

4R Nutrient Management in Agriculture

The 4R nutrient strategy is an important framework for optimizing the use of fertilizers in modern agriculture. By following this approach, farmers can ensure that they are using fertilizers in the most efficient and effective way possible, resulting in improved crop yields and reduced environmental impacts.

Using the 4Rs in an on-farm nutrient management strategy is a science-based way to put plant nutrients to work while being economically and environmentally sustainable. Over time, proper nutrient management through the 4R strategy can support improved soil health and enhanced soil organic matter. 

The 4Rs and AgTech

In order to successfully implement the 4R approach, it is important to use advanced decision support systems and digital platforms. These tools can help farmers and growers to accurately assess the nutrient needs of their crops and the characteristics of their soil, and to determine the most appropriate type, rate, time, and place for applying fertilizer.

For example, precision agriculture technologies such as satellite imagery, drone-based mapping, and sensors can be used to gather real-time data on soil nutrient levels, crop health, and other factors. This data can be used to generate detailed maps of the fields, which can be used to identify areas that are in need of specific nutrients, supporting the right placement of fertilizer. 

Precision agriculture technology can also support the 4Rs at the point of application. GPS and robotics technologies help deliver nutrients to the precise place they are needed at the correct rate. Capturing application data to compare with yield data helps inform future decision-making. 

In addition, digital platforms such as software applications and online tools can be used to track and record the application of fertilizers, as well as to monitor the performance of crops and soil over time. This information can be used to fine-tune fertilizer application strategies and optimize the use of fertilizers to achieve the best possible crop yields and soil health.

Agmatix’s Digital Crop Advisor platform is a digital decision support system that enables easy application of the 4Rs on-farm. Agronomists and field technicians can help farmers make data-driven decisions around the rate and placement of nutrients. 

Crop nutrition plans created with Digital Crop Advisor harness the power of data on over 150 crops to determine the right timing and source of nutrients based on specific crop needs. Plans can even include controlled-release fertilizers and a view of nutritional distribution across phenological crop stages as part of 4R nutrient management.

Digital Crop Advisor provides a view of the impact of 4R nutrient management on sustainability KPIs, too. It’s possible to run multiple simulations to compare the environmental and yield impacts of different approaches. Sustainable nutrient recommendations take carbon footprint into account as well. 

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4Rs for the Future

The 4Rs provide a clear path to better use of fertilizer in growing food, fuel, and fiber for the world. Employing this strategy addresses food security for the world’s growing population through optimally using applied nutrients to balance crop production, soil health, and natural resources. 

The use of advanced decision support systems and digital platforms can greatly enhance the effectiveness of the 4R nutrient management approach. Automated fertilizer plans created with the Digital Crop Advisor crop nutrition recommendation tool make considering all aspects of the 4Rs and implementing the approach simple. 

Ultimately, the combination of the 4Rs and enabling technologies help farmers and growers to use fertilizers more efficiently and sustainably, and to achieve better crop yields and soil health for the future of the growing world. 

This blog was written by 

Liran Shmuel, Lead Agronomist at Agmatix has over 10 years of experience in startups and consulting. Liran has a proven track record of developing innovative solutions in AgTech that improve crop yield and sustainability. He is passionate about helping Ag professionals overcome obstacles in sustainable food production.

Top 5 Ways Crop Nutrient Planning can Reduce Agriculture’s Carbon Footprint

“Growers, agronomists, researchers and ag industry experts are tackling today’s biggest challenge – providing food security for the world’s growing population,” according to Ron Baruchi, CEO of Agmatix. 

Food security in the 21st century goes beyond just growing more crops. Growers, agronomists, and industry experts must unlock a path to increased productivity and quality while at the same time reducing the environmental impacts of agriculture in order to sustain production for the future. 

Crop nutrient planning, supported by digital tools, is one way in which agronomists and industry experts can help growers to increase yields while reducing agriculture’s carbon footprint. 

What are Crop Nutrient Planning and the Carbon Footprint of Agriculture?

Crop nutrient planning is a holistic approach to optimizing the economic, agronomic, and environmental requirements related to nutrients used for crop production. Historically, crop nutrient plans may have been informal or focused solely on agronomic or economic requirements. Now, crop nutrient planning supports maximizing nutrients’ economic benefits while minimizing environmental impact. 

Carbon footprint is defined as the total amount of greenhouse gases generated by a person, organization, action, or product. Carbon dioxide, methane, and nitrous oxide are all examples of common greenhouse gases. High carbon footprints increase the global temperature. Agriculture has a measurable carbon footprint, and it’s sizable. An estimated 31% of human-caused greenhouse gas emissions are tied to the global agri-food system. 

Crop nutrient planning can be a blueprint for how to reduce carbon footprint in agriculture. By setting a crop nutrient planning objective of increasing nutrient efficiency and effectiveness and reducing environmental impact, agricultural greenhouse gas emissions can be reduced. 

And because synthetic nitrogen fertilizer manufacturing is a significant source of greenhouse gas emissions, planning for this crop-essential nutrient with the environment in mind is especially important. 

5 Ways Nutrient Planning Can Reduce Agriculture’s Carbon Footprint

  1. Maximizing arable land use: through increasing efficiency, growing more food on the same amount of land is possible. Nutrient planning to increase yield can maximize production per acre while minimizing environmental impact. 
  2. Implementing a 4Rs approach: precision is an important part of crop nutrient planning. The 4 Rs refer to the right place, right rate, right time, and right source. Considering the combination of the 4 Rs to inform management decisions can minimize the carbon footprint of agriculture. For example, the right source can reduce the use of synthetic fertilizers whose manufacturing contributes to greenhouse gas emissions. The right rate, right time, and right place can reduce nutrient leaching
  3. Practicing good land stewardship: crop nutrient planning promotes sustainable practices that respect the land. Using fewer chemicals and intentionally protecting natural resources increase biodiversity in the environment. 
  4. Reducing waste: over-application or wasted nutrients are not only unprofitable for farmers – they have detrimental impacts on the environment, too. Wasted nutrients are nutrients that plants are unable to use and potentially become environmental pollutants that degrade water quality. 
  5. Using a data-driven support system: using high-quality agronomic data to support management decisions can help farmers reduce their carbon footprint. Data-driven support systems can be used to optimize crop nutrition. Running simulations to compare nutritional recommendations and understand tradeoffs between yield and environmental impact is one example of how data-driven decisions play out at the agronomist and farm level. 

Mission Critical: Reducing Agriculture’s Carbon Footprint

Agriculture is both a contributor to and at risk from a changing climate. Today, agriculture is estimated to be responsible for roughly 18% of greenhouse gas emissions. Agriculture’s emissions contributions have grown 30% in the last forty years. 

This runs contrary to the U.N.’s goal to reduce emissions by 45% by 2030 and reach net-zero emissions by 2050. Reaching net zero will prevent the Earth from warming past 1.5 degrees Celsius above pre-industrial levels. Right now, commitments and actions fall short of what’s needed to reach net zero. Reducing the carbon footprint of agriculture will help reach these emissions goals. 

Agriculture is also particularly vulnerable to the impacts of a changing climate. Corn, soybean, rice, cotton, and oat yields are already expected to be reduced due to global warming. And climate impacts could cause an uptick in irrigation needs at the same time water availability is limited. 

Improving on-farm efficiency through technology could reduce emissions from agriculture by roughly 20% by 2050. Among other examples, this could include steps to reduce nitrogen over-application in China and India, reducing or stopping tillage, improving rice straw management, and improving the fertilization of rice. Many of the opportunities to increase efficiency and decrease the carbon footprint of agriculture tie directly to nutrient planning and management. 

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Digital Crop Advisor Can Help 

Determining how to reduce carbon footprint in agriculture can be challenging without the right tools. Using agronomic field trial data to support crop nutrition planning helps farmers apply the precise nutrients plants need with the lowest possible environmental footprint. 

Agmatix’ Digital Crop Advisor solution makes it easy for sales agronomists and other advisors to calculate fertilizer carbon footprint. It’s simple to compare sustainability KPIs – like nitrogen leaching, for example – against historical nutrient plans or current nutrient plans in other fields. 

With this tool in hand, nutrient planning can take into account the field characteristics, fertilizer and crop types, and more. Science-backed nutrition plans containing all crop-essential nutrients help maximize yields while minimizing agriculture’s carbon footprint. 

12 scientifically-proven crop nutrient data profiles enhance agriculture crop protocol management with unbiased product catalog-based recommendations. Nutrition plans are available for over 150 crops and can include carbon footprint-reducing options like controlled release fertilizers. Various simulations are available to deeply understand potential tradeoffs between yield growth and environmental impacts. 

Digital Crop Advisor is a key tool to address the five ways nutrient planning can reduce agriculture’s carbon footprint. As a data-driven support system intended to optimize nutrient management, Digital Crop Advisor supports land stewardship, maximizing productivity, and reducing waste. The 4 R’s are the bedrock of the recommendations. Digital Crop Advisor is a way to seamlessly support the reduction of agriculture’s carbon footprint. 

The Power of Big and FAIR Data Collaboration

Isaac Newton, one of the most influential scientists in history, once said “If I have seen further, it is by standing on the shoulders of giants.” 

This holds true in agriculture and agritech analytics. Through collaboration and open-access data, scientists are able to continue building on the achievements made before them to better our world. In agriculture, building on these achievements allows scientists and researchers to address critical problems with data – including food scarcity, feeding a growing population, reducing agricultural greenhouse gasses, and adapting to a changing climate. 

Big data has a lot of power in agriculture. Big data can be viewed as the combination of technology and analytics that can collect and compile novel data and then process it to support decision-making. Big data can provide farmers with information on factors that impact crop yields, such as soil moisture or weather changes. However, big data requires standardization, harmonization, and analysis to be valuable – and it takes a lot of resources to accomplish this due to the massive size and complexity of big data. 

Alongside big data comes the need for FAIR data. The FAIR Guiding Principles were published in 2016 to address scientific data management and stewardship. FAIR stands for Findability, Accessibility, Interoperability, and Reuse of digital assets, according to the FAIR principles. They call out that data and metadata should be easy to find for humans and computers, and the finder should know how to access the data. Then, the data needs to be integrated with other data, including workflows and applications for storage and analysis. And ultimately, FAIR promotes the reuse of data, requiring data to be well-described for replication or combination in alternate settings. 

For agriculture research, big data is the fuel that can be successfully used when the FAIR data principles are in play. Ag data analytics is a powerful tool to solve major challenges in the world, but only when data is interoperable and reusable. This can be a challenge given the size and complexity of agricultural big data. Luckily, Agmatix, an agro-informatics company, is focused on turning big data into powerful insights. 

How Agmatix’s Axiom Platform Can Help

When using unfamiliar data for modeling efforts or meta-analysis, it is all about findability, accessibility, and interoperability – the F, A, and I of the FAIR principles.  For researchers embarking on the agritech analytics journey, it is essential to get acquainted with the data producers, time frames, relevant metadata, and relevant methods and protocols. This information is the basis for finding and accessing the right data. 

Agmatix’s Growing Universal Agronomic Data Standard (GUARDS) protocol is based on the FAIR data principles. It uses ontologies and hierarchy definitions to classify data components. This reflects findability and interoperability. Datasets are automatically screened and categorized to create direct links between metadata, as well as independent and dependent parameters. 

By using the Insights module, data scientists access a user-friendly interface to visualize big datasets, descriptive statistics, and graphic content visualization. They can access standardized datasets without the time consumption and effort of individual dataset standardization. It’s even possible to share notions and conclusions between users. There are several statistical tests available for data analysis, and users can create a knowledge graph based on the ontologies and analyzed data. Ultimately, the Insights module supports data scientists in accessing diverse datasets. 

Agmatix’s Axiom platform is different from other ag data analytics platforms and agronomic analysis tools. Agmatix is the first company to apply data standardization according to the FAIR principles over agronomic legacy data and ongoing trial data collection processes. The Axiom database is the first multi-disciplinary agronomic database that allows meta-analysis alongside modeling and data sharing. Sophisticated data validations and integrity tests are performed to ensure the highest data quality according to the FAIR standards. In the heart of Axiom, an ontology codebook is used to understand and define relations between data points. 

Case Study: Corn Prediction Model Using Axiom Platform

Big and FAIR data through the Axiom platform was the basis for a recent corn yield prediction model. The model unified data from many sources across various production environments in the U.S. 

Data included farm management and experimental data from collaborators and open repositories of publicly available data. Common parameters were identified between these datasets. They included total Nitrogen applied, previous crop, soil texture, soil organic matter, and irrigation data. The base data was enriched with weather data, including precipitation and temperature at specific corn stages. The key factors in any model will change as inputs change. 

In this corn prediction model example, using unified data from multiple data sources, corn yield can be estimated at an accuracy of 16 bushels per acre – and higher if looking specifically at a single region. 

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Knowledge Is Power, Use Data To Fuel Better Decisions

Agmatix Enables Collaboration

Agmatix drives agronomic innovation by moving research and experimental data into real-life action. The power of data is core to Agmatix’s beliefs, driving innovation in data access and decision support through agronomic analysis tools. Agmatix encourages and supports the implementation of the FAIR principles in a few different ways. 

The GUARDS protocol which governs data standardization is based on the FAIR data principles. Of particular focus are the F and I in FAIR: the representation of the metadata (Findability) and ontology allocation (Interoperability).

The INSIGHTS and MODELS platform completes the FAIR acronym. It allows access to diverse datasets (Accessibility) and sharing between projects and users (Reusability).

Agmatix’s TMP platform for planning and executing new and ongoing trials preserves the data according to the GUARDS protocol on the go. This platform unlocks the power of agronomic trials and big data. 

Agmatix is dedicated to growing data for impact – a fertile ground, rife with possibilities, when with big data and the FAIR principles. 

Unlock True Value from Agricultural Data with Agmatix

Raising a high-quality, high-yielding crop depends on healthy soils and healthy plants that perform well in their environment. Understanding how to support plant and soil needs for maximum productivity can be complex. 

Plants are affected by a multitude of factors that can enhance or limit their yield, or overall success. Generally speaking, these factors can be categorized as technological, biological, and environmental factors. 

Technological factors include agricultural practices and managerial decisions, such as tillage intensity or nutrient management. Crop diseases, pests, and weeds are all biological factors while environmental factors include climate, soil, water, and input nutrients. Understanding and managing these factors is critical for delivering a high-quality, maximum-yielding crop. 

Agmatix’s cutting-edge technology helps you analyze these factors and associated data within your crop dataset. Ultimately, this provides you with powerful agronomic insights and possible crop models to unlock true value from your data!

Data on the Farm?

Data is an increasingly important part of decision-making on the farm and in the agricultural industry. Data illuminates historical trends, clarifies hidden values, and provides an additional perspective to traditional observations and contextual information. 

Agriculture produces massive amounts of big data related to climate, weather, yield, and price. There is a multitude of uses for big data in agriculture from production efficiency to sustainability for the future. Data can be used for overcoming challenges in agriculture related to climate change, quality, and understanding markets. 

Big data in agriculture rarely comes from a single source or collection method. Rather, there are many agricultural data collection methods. These include collection by hand or manually, with a drone, with farm machinery or an IoT sensor. This data can cover all three plant-impacting factors: biological, technological, and environmental. Having a 360-degree view of factors influencing plant growth from differing agricultural data collection methods further fuels informed decision-making for the future. 

Technology and data in agriculture have the potential to yield higher returns. According to McKinsey research, the connectivity that drives data collection, collaboration, and utilization can add $500 billion incremental value to global GDP by 2030. 

Crop monitoring is one of the key use cases that will drive this value through higher yields, lower costs, and increased sustainability and resilience. That value will be derived from fruit, vegetable, cereal, and grain crops grown around the world. Other use cases for digital growth include animal health, chemical usage, carbon footprint management, water quality, and even exports. 

Armed with connectivity, agricultural data can increase precision and tracking on the farm. Precise and efficient autonomous machinery can be powered by reliable and responsive connectivity. And agriculture data can expand its reach – into even the most remote, rural areas where food is grown and farmers can adapt their decisions for the future. 

As of 2020, roughly one-fourth of U.S. farms are using connected devices for data collection and management. The cost of connectivity hardware is decreasing to a point that a return on investment through the collection and use of data can be seen in the first year. New connectivity technologies are expected to evolve throughout the next decade, unlocking additional opportunities and value for data in agriculture. 

More Data, More Opportunities

Data can address current and future pressures on the agriculture industry, such as a growing world population and mouths to feed while land availability is limited. Farmers face a projected 70% increase in needed calories for consumption by 2050, all while environmental pressures increase. 

A changing climate and catastrophic weather events add increasing risk to the world’s food supply. By 2030, the world’s water supply will drop to 40% short of meeting global needs. And one-fourth of the world’s arable land is too degraded to grow crops at scale without major restoration. Challenges – and thus, opportunities – abound for agriculture in the next few decades. 

Through collecting and analyzing data on various aspects of the growing season, it’s possible to approach complex challenges – like climate change. Data and the Internet of Things are already being used to optimize production cycles as traditional calendars and practices are no longer sufficient. 

Soil data science is deepening scientists’ understanding of soil’s contributions to climate change through releasing and sequestering greenhouse gasses. Scientists, agronomists, and growers use the better understanding of this relationship to take proactive and productive steps to reduce carbon footprint in agriculture. 

Agronomic data analytics also allow growers of any size to be hands-on with the health of their fields during the season – without actually being hands-on. It’s possible to monitor crops at scale and capture the data to use for future decision-making. From managing crop diseases and pests to making yield predictions in support of marketing decisions, agricultural data unlocks a whole lot for farmers and the agriculture industry. 

Agmatix Can Help!

It’s difficult to make decisions without data, but it’s also difficult to sift through mounds of data to make a decision. Agmatix can help you easily unlock the value of your data!

The Agmatix platform provides a view of all of your data in one unified place. Develop a deeper understanding through agronomic data standardization of information from field trials and agronomic databases. 

Actionable reports and recommendations are paired with a user-friendly interface for statistical analyses of the dataset with no code required. Pre-built analytical widgets allow anyone to find use of data science capabilities and then share custom reports – that can even be adjusted on the fly. These statistical tools increase the integrity of on-farm experiments and double down on data quality in agriculture. 

Multi-location trials over several years often lead to data floating around and even getting lost. With Agmatix, agriculture analytics for all of your trials can be viewed in a single workspace. That trial data can be shared easily so you can work with your collaborators directly for cross-trial analysis. This collaboration will improve decision-making and decrease the time from data to insights to direct action. 

Agmatix believes in the power of open data in agriculture and has worked collaboratively across the industry to increase the availability and impact of data. Collaboration across researchers and agriculture professionals built on a foundation of standardized agronomic data empowers innovation around the globe. The world’s best minds can leverage enriched agriculture datasets to provide the most accurate information to farmers and support their decision-making. Ultimately, this leads to improved yields, profits, soil health, and environmental outcomes. 

For example, the Global Crop Nutrient Removal Database is an agronomic database created in collaboration with the International Fertilizer Association, Wageningen University & Research, the African Plant Nutrition Institute, and Innovative Solutions for Decision Agriculture. 

The basis of the project is to understand the relationship between nutrient inputs and outputs in crops under differing production and environmental conditions. Knowing how crop nutrient removal from one crop can influence the next crop on that land enables agronomists to determine the most precise rates of specific nutrients needed to sustain healthy soils and crops. 

Data analytics in agriculture, powered by the right tools, unlocks high-yielding crops and better management of technological, biological, and environmental factors. Agmatix is dedicated to growing data and the power of data use to drive impact in agriculture. Field-level decisions with focus on the future can be fueled by data science technology and agriculture analytics to address today’s agriculture challenges and tomorrow’s opportunities. 

How Precision Farming Tools Can Help Agriculture Become More Resilient

Resilient: defined by Merriam-Webster as “capable of withstanding shock” and the ability to “recover from or adjust easily to change.” Resilience enables people to adapt to setbacks and bounce back from changes. In business, resilience protects continuous business operations, people, and assets. It separates those that can innovate and thrive from those that freeze and fail. 

Resilient is what agriculture must become to withstand changes in climate, rising costs, supply chain challenges, and a growing population demanding more production on less land. And while building resilience is not easy, having the proper tools at hand makes withstanding the storm much easier. 

The development and implementation of agriculture technology in recent decades has paved the way for farmers to improve their productivity and sustainability like never before. This wave of precision farming tools – often referred to as precision ag or precision agriculture – is what enables agriculture to become more resilient to changes. 

What Is Precision Agriculture?

The International Society of Precision Agriculture defines precision agriculture as “a management strategy that gathers, processes, and analyzes temporal, spatial and individual data and combines it with other information to support management decisions according to estimated variability for improved resource use efficiency, productivity, quality, profitability and sustainability of agricultural production.”

Precision agriculture technology leverages new technologies to increase crop yields and profitability while reducing the amounts of inputs needed for crop production. Reducing inputs can be crop-dependent, but often means minimizing the land, water, fertilizer or crop protectants needed to maintain or increase yields. Oftentimes, this requires resources to be used more effectively or precisely.

There are many examples of precision agriculture technology in use today. GPS systems on farm equipment can help farmers plant in efficient patterns to save time and fuel. Documenting where the tractor or sprayer has been through the GPS system can reduce overlapped seeds during planting or reduce overapplication of fertilizer and crop protectants. 

Unoccupied aerial vehicles can be used to fly over fields and measure disease on crops. Farmers can monitor plant health of the entire area without needing to walk through every pass on foot. With a birds-eye view, farmers can make the most sustainable and profitable crop protection decision. 

Water management can be part of precision agriculture, too. Soil moisture sensors can be used to measure current soil moisture and assist in irrigation system scheduling to ensure that water is distributed only when needed to reduce inefficient or excess application. 

In many of these examples and across the industry, precision agriculture and sustainability often go hand-in-hand. Reducing or precisely placing inputs, reducing fuel use, and improving decision-making is a win-win for farmers and the environment. 

Data Is What Makes Precision Agriculture Possible

Precision ag encompasses many different types of technologies. The collection of data for these technologies – or by these technologies – is the fuel that makes precision farming so powerful. 

Armed with data that spans multiple years, numerous crops, all applications, and different climatic events, models and machine learning can improve accuracy in outputs for farmers. Correctly identifying diseased plants from images or understanding what plants in a field are weeds versus crop lets a farmer address crop needs efficiently and effectively – with minimal input use. 

Predicting fertilizer needs based on crop developmental stage allows farmers to provide the nutrients needed at the right time and right rate for maximum effectiveness. These are all data-based precision agronomy solutions.

Data can be quantitative or qualitative, but are typically composed of single observations or numbers reflecting an important variable in the production process. Data has been used for decision-making on the farm since the 1990s, but recent advancements in communication and sensing technologies have made on-farm data collection cost-effective and increasingly popular. 

Today, big data analytics in precision agriculture improve efficiency and productivity, increase cost control, improve execution, and automate farming activities. Agriculture data management goes hand-in-hand with these benefits of precision agriculture crop management, though tools are becoming increasingly optimized for data management on the farm. What’s most critical is creating and utilizing accurate data because it is the bedrock that makes precision agriculture possible. 

Agmatix’s Tools For You

Big data analytics in precision agriculture have so much potential to improve sustainability and profitability. Agmatix develops technologies that convert data into field-level actionable insights through agronomy data science and artificial intelligence.

Agmatix’s Digital Crop Advisor is a precision agronomy crop nutritional decision support tool. Digital Crop Advisor creates customized nutrition optimization plans and standardizes field measurements. Multiple parameters are considered in the creation of the nutrition optimization plans, including crop type, field location, pH, previous crops, plant uptake, and laboratory analyses. 

Users can monitor sustainability KPIs such as carbon footprint and nitrogen leaching. WIth this precision agriculture tool, it’s even possible to understand the tradeoffs between driving high yields and minimizing environmental impact. 

Digital Crop Advisor also provides insight into crop production at any scale. Deep insights into yield, quality, and carbon emissions are possible, even across worldwide operations and a diverse team. This easy access to data enables efficient and effective decision-making. 

Agmatix is a proponent of open data to enable precision agriculture crop management. Agmatix offers an open data platform for agriculture professionals and researchers around the world. Users can easily share and access standardized agronomic data to support data analytics in precision agriculture. By breaking down data silos, the full value of precision farming is unlocked. 

Agmatix also supports open data access through partnerships with the International Fertilizer Association, Innovative Solutions for Decision Agriculture, the African Plant Nutrition Institute, and Wageningen University & Research. The Global Crop Nutrient Removal database is an example of open-source agriculture data that can be used to make informed, precise crop management decisions. 

Digital Crop Advisor transforms open data from all sources: live inputs from growers, existing databases, and data silos. This data combined with advanced algorithms takes precision agriculture crop management to the next level. 

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Precision Ag for the Future 

Precision agriculture benefits farmers and sustainability through reduced input costs, increased productivity and profits, more sustainable cropping systems, and lower carbon footprints. Precision farming can help farmers at any level be more resilient to the ever-changing world. With precision agriculture technology, a successful cropping system is possible, regardless of external factors requiring adaption. 

That’s why Agmatix is focused on providing precision agronomy solutions that use the power of big data analytics for field-level insights. With the right tools, fueled by data, agriculture can position to be successful despite an uncertain future. 

10 Steps for Easy On-Farm Trials Execution

On-farm research is a powerful tool for farmers. For one Brandon, Manitoba farmer, conducting on-farm trials provided the data needed to confidently cut canola seeding rates without cutting yield potential or extending maturity. One Illinois farmer points to $100-$150 per acre increased profitability through on-farm trials he’s been running since 1985. 

For many farmers, on-field experimentations are an excellent way to test out a new product or production practice on their own land. Farmers can generate their own science-backed, relevant information that supports decision-making to improve yield and crop quality. 

With precision agriculture technologies and big data, it’s easier than ever to successfully conduct agricultural field trials. Farmers can precisely plan and execute on-farm trials using GPS technology, and collecting data becomes simple with mobile applications and IoT sensors. Farmers and agronomists can use agronomic databases and agtech tools to standardize data or enrich their own data with multiple source datasets. 

There has never been a better time to start using on-farm research as a management tool to improve profitability and sustainability. Using proper on-farm trials methodology is critical to ensure results are accurate and reliable. The steps below outline how to conduct successful on-farm trials – from design to execution to data analysis!

1. Keep a clear direction in mind

Starting off an on-farm trial with a clear direction is a critical first step! Identify what specific practice or treatment you want to evaluate or test with on-farm research. Ensure that all participants and stakeholders understand what’s being evaluated and why it’s important. For example, a trial could be vital due to its connection to profitability or sustainability.

2. Ask the right scientific question

On-farm trials should start with a specific, scientific research question with a yes or no answer. The research question is often a comparison between two agronomic practices, such as: will yield be reduced when strip-tillage is used? Once the scientific question is identified, plan for the relevant variables to be measured in order to answer that question.

3. Determine the data collection process

To minimize confusion and ensure accuracy in data collection, determine standard operating procedures (SOPs) to gather data. These should be pre-determined approaches that are always used, regardless of who is gathering the data. For example, ahead of collection, data record sheets should be prepared, sample bags should be labeled, and harvesting procedures should be determined.

4. Plan for replication

Replication is a best practice for answering the research question when conducting on-farm trials. It involves repeating plots of the control AND the treatment across the farm, which provides a large dataset. Replication helps take into statistical consideration the variability that exists on the farm, such as soil variations or weed pressure differences, that could bias the results of the trial.

5. Be ready to randomize

Randomizing plots of the treatment and control is another way to control for field variability. Randomization refers to the placement of treatments and controls in blocks, which are randomly assigned in the trial area. This helps remove any bias for one practice or treatment over the other. Randomization and replication can be used together.

6. Know the site 

Take an inventory of the field history, variability, and other factors that might impact the results. Fully understanding the farm where the on-farm trial is taking place is critical for the results to be meaningful to other farmers. Documenting factors like geographic slope, soil type, drainage class, crop rotation history, tillage practices, chemical application practices, and other similar information is important for context.

7. Capture data and observations

On-farm research is time-sensitive. Collecting necessary data at the property times for the research question is critical because once that opportunity has passed, it’s not possible to get it back. Taking note of other observed factors that could influence the on-farm trial is important, too – even if those changes weren’t anticipated. 

8. Analyze results

Once data is collected, it’s time to dig in and answer that research question. There are various statistical approaches to determine if a treatment or practice had a significant impact on performance. Using statistics in data analysis is recommended because it creates confidence in the outcomes.  

9. Share the outcomes

Discuss findings and observations with farmers and researchers to wrap up the on-farm trial. This is also a good time to determine any next steps, which might include repeating the trial in a different area or deciding to put the production practice or change it into practice across a larger part of the farm.

10. Put findings to work!

The last step in conducting on-farm trials is turning the results into actions. Apply findings to future research on the same farm – or broaden the research opportunity by gaining traction with others.

With these steps outlining how to conduct successful on-farm trials, it’s possible to take farm profitability and sustainability to the next level. 

At Agmatix, we support on-farm experimentation with the user-friendly, flexible mobile app as an extension to our  Agronomic Trial Management solution. Farmers running trials can easily plan, manage, and collect data from trials. 

Agronomic trial management is critical to ensure the results of on-farm trials maintain scientific integrity and can be counted on to support decision-making. On-farm trial methodology can seem complex. But with the Agmatix mobile application, it’s easy to stay connected and follow the 10 key steps to on-farm research!

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Why Collaboration is the Key to Innovation

Collaboration – or working together with someone else to produce or create something – is key to innovation. Working jointly in intellectual endeavors means connecting the world’s best minds, all working from the same page, to solve problems and overcome barriers. 

At Agmatix, we’re firm believers in the power of collaboration, built on a foundation of open-source agriculture data. Better agronomic data and strong connections between researchers and agriculture industry professionals lead to better yields and profits, sustainable production and improved soil health, and ultimately positive outcomes for the environment. 

Collaboration Keeps Science Moving

Dr. Kenneth Wilson, 1982 Nobel Prize in Physics recipient, said “the hardest problems of pure and applied science can only be solved by the open collaboration of the worldwide scientific community.” 

This is certainly evident in agriculture science. Collaboration has been key throughout agriculture’s history. For example, Dr. Evangelina Villegas and Dr. Surinder Vasal, with their teams at the International Maize and Wheat Improvement Center (CIMMYT), improved the productivity and nutritional content of maize through the development of quality protein maize in the 1980s. This collaboration supported the national security of communities that depend on maize. 

Maize protein is an example of collaboration in agriculture science leading the way for innovation. In the future, new challenges in agriculture will have to be addressed – and collaboration can help to overcome them. Feeding a growing population and protecting the environment come to mind as key challenges that agriculture will face in the near term. 

The United Nations projects a global population increase from 8 billion people to 10.4 billion people by the century’s end. No additional land is available to feed that growing population. Collaboration will be required to create solutions that feed more people on the same or less land.  

While feeding a growing population, agriculture will also need to protect the environment. Agriculture currently contributes around 11% of global greenhouse gas emissions. Deforestation, livestock manure, and household consumption are leading sources of greenhouse gas emissions in agriculture

Sustainable agriculture production will need to lead the way in reducing agriculture’s carbon footprint and protecting natural resources. 

Agmatix’s Tools Enable Collaboration

Collaboration is fueled by shared knowledge and information. It takes the right tools to connect people and data. Agmatix supports scientific collaboration in agriculture through our Axiom technology, Agronomic Trial Management tool, and Insights capabilities. 

Axiom Technology converts big data into actionable insights. The Growing Universal Agronomic Standard (GUARDS) protocol is an ontology hierarchy system for agriculture data harmonization that aggregates and standardizes all research data, so it can be used for collaboration. 

One component of the GUARDS protocol is to convert different measurement units into a single unit and standardize the data values accordingly. For international agriculture research teams, working in metric or imperial measurements is no longer a concern – everyone can be on the same page. Through Axiom Technology and the GUARDS protocol, all data is speaking the same language and is apples to apples. 

Agmatix’s Agronomic Trial Management is a tool for trial coordinators, research scientists, CROs, and field technicians collaborating on on-farm experiments. An easy-to-use interface enables quick communication with others on the team. Users can track task assignments across team members and receive updates related to ongoing field trials. Sharing data with team members and partners is simple, allowing for real-time visibility and control. 

For trial coordinators and research scientists, the Insights platform is a powerful tool for agricultural data collaboration. Data from all field trials are housed in a singular, unified platform. It’s easy to visualize and share all of an organization’s trial data with the team or CROs in just a few clicks. 

Field technicians, agronomists, marketers, and executive managers can use the Digital Crop Advisor platform to drive a proactive business and deeply understand their crop production markets. Management, sales agronomists, and marketing have visibility to where products are selling and what crops they’re being used in. Digital Crop Advisor allows the whole team to collaborate on proactive product supply planning driven by customer needs and real-time data. 

Agmatix’s Collaboration Culture

Agmatix doesn’t just provide tools for agriculture professionals to effectively collaborate – we’re actively working with others in the industry to enable open-source agriculture data that spurs innovation. Through partnerships with other organizations, two databases have been developed to support ag data analytics

The Global Crop Nutrient Removal Database was created through collaboration between Agmatix, the International Fertilizer Association, Innovative Solutions for Decision Agriculture, African Plant Nutrition Institute, and Wageningen University & Research. By looking at production and environmental factors that affect nutrient concentrations, it’s possible to determine the total amount of nutrients removed from the field in the harvested portion of the crop. 

This source of open agriculture data highlights the connections between inputs and outputs of crop nutrients in varying production environments. Armed with this data, crop nutrition work and management can be optimized for sustainability and crop productivity. 

Another example of open agriculture data is the Nutrient Omission Trial Database. Its goal is to provide data that supports site-specific agricultural recommendations and optimized nutrient management. The database was created in collaboration with the International Fertilizer Association, the African Plant Nutrition Institute, Innovative Solutions for Decision Agriculture, and Agmatix. 

The database enables agriculture researchers to compare crop nutrient requirements and plans to support site-specific recommendations. The database notes variations in soil fertility and other farm-specific environmental conditions. A single, open, standardized data set was created through the GUARDS protocol consolidating legacy nutrient omission research data from various sources. This streamlines integration into advanced fertilization tools and improves collaboration between Consortium for Precision Crop Nutrition members. 

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Collaboration Leads the Way 

To continue making progress in providing food sustainably for the world, collaboration is essential, and Agmatix’s tools can help. Agmatix believes in a collaborative future of agriculture supported by open agriculture data for researchers and agriculture professionals around the globe. 

Through connecting people and data, Agmatix enables the type of collaboration that created quality protein maize. Agmatix takes data analytics in precision agriculture to new heights. 

With tools like Axiom Technology, Agronomic Trial Management, and Digital Crop Advisors, industry professionals can collaborate in new ways. Key sustainability and crop production decisions are supported by open-source agriculture data from the Global Crop Nutrient Database and Nutrient Omission Trial Database. With a foundation of collaboration tools and agriculture open data, the future is bright for innovation in agriculture. 

Integrated Nutrient Management and its Role in Sustainable Agriculture

Sustainability in agriculture is of increasing importance in the 21st century. As agriculture works to provide food, fuel, and fiber for a growing population, managing limited natural resources and caring for the environment are critical considerations. 

Sustainable agriculture practices can protect the environment, increase farm profitability, and increase crop production on critical food and fiber needs. In the long term, sustainable agriculture practices protect crop production, the environment, and economic viability. 

After many years of soil compaction, sustainable practices are needed to address nutrient deficiencies to apply adequate amounts of fertilizers. Increased nutrient use efficiency is needed. Integrated nutrient management for sustainable agriculture addresses these challenges by optimizing fertilizer inputs without reducing crop yield. 

What is Integrated Nutrient Management?

Integrated Nutrient Management, or INM, is a sustainable agriculture method for achieving production needs and protecting the environment for future generations. INM is the application of soil fertility management practices that maximize fertilizer and organic resource use efficiency to enhance crop production. 

Agriculture is a soil-based industry. Soil is the foundation of crop production, as it provides plants with the necessary environment, nutrients, and water for survival. Soil provides anchorage for plant roots and provides ecosystem services that sustain life on Earth. 

While soil does naturally contain a certain amount of nutrients and minerals, specific needs for nutrients and their quantities vary across crops. Even healthy, naturally nutrient-rich soils may need to be supplemented with additional fertilizers.

Integrated nutrient management for sustainable agriculture helps meet soil nutrient needs in an environmentally-conscious way. The FAO notes that INM uses the benefits from all possible sources of plant nutrients to maintain or adjust the plant nutrient supply needed to achieve the desired crop production level. 

This happens through a few different mechanisms, including improving the stock of plant nutrients in the soil, maintaining or improving soil fertility, and increasing plant nutrients. 

These approaches should include a balanced use of mineral fertilizers along with organic and biological plant nutrient sources. By addressing plant nutrient efficiency, nutrient loss to the environment – and the subsequent environmental concerns – are limited. 

The UN Climate Technology Centre and Network indicates another component of INM is participatory, farmer-led INM technology experimentation and development. This on-farm experimentation helps test locally appropriate technologies and empowers farmers by increasing their technical expertise. This supports optimal nutrient source use on a crop system or rotation basis, rather than looking singularly at a single crop. 

The Challenge 

The world’s future food needs will be hefty: feeding nearly 10 billion people by 2050, according to the UN, will require production to grow substantially. But growth alone is not enough; minimizing negative impacts on the environment is what will secure food, fuel, and fiber for generations to come.

Limited arable land and declining natural resource availability underscore this challenge. The International Food Policy Research Institute indicates that the land currently in use will need to be more productive and strategies to grow productivity will need to be linked to using nutrient resources more efficiently than in the past. 

When farmers overuse certain inputs, they can deteriorate the sensitive soil-plant-microbe environmental systems that are vital for productive, sustainable ecosystems. INM helps create balance in the input source and rate to protect the environmental systems that are so critical for plant and microbial life. 

Managing Nutrients and Sustainability with Agmatix

Agmatix, a global agro-informatics company driven by turning agronomic big data into insights, can help make INM a reality on the farm. With crop management software, an automated fertilization plan can meet both sustainability and crop production goals while adhering to the principles of INM. 

Agmatix’s Digital Crop Advisor platform is a crop nutrition recommendation tool that uses data to optimize crop nutrition, increase profit, and lower environmental footprint. Expert knowledge, cutting-edge technology, and local data insights collide in a single plant-integrated nutrient management software, making fully-customizable nutrition management fast and easy. 

With the Digital Crop Advisor crop nutrient management tool, it’s easy to access crop nutrition management plans for a field. The software has 150 crop options and 12 scientifically-proven crop nutrient data profiles for plant-integrated nutrient management. It’s even possible to view nutritional distribution across crops’ different phenological stages. 

With smart fertilizer software, farmers can monitor sustainability KPIs, such as carbon footprint and nitrogen leaching, with recommended crop fertilization plans. It’s also possible to compare various simulations and recommendations to understand options. This plant nutrient management tool makes it seamless to see the tradeoff between maximizing yields and minimizing detrimental environmental effects.

And connecting INM across a global team and directly with growers is seamless with the Digital Crop Advisor management software. Multiple devices, including a mobile app, are supported. Different languages are available. Viewing the real-time status of worldwide operations is easy, meaning INM is possible at whatever scale is necessary. 

Agronomic big data plays a big part in enabling INM on the farm. Open and comprehensive data is available through the Global Crop Nutrient Removal Database, created through collaboration between Agmatix, the International Fertilizer Association, Wageningen University & Research, African Plant Nutrition Institute (APNI), and Innovative Solutions for Decision Agriculture. Using this dataset to understand crop nutrient removal rates in the short- and long-term supports improving crop nutrient management and optimizing for sustainability. 

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At Agmatix, we understand the drive to optimize crop yield and nutrition while being good stewards of the land. We strive to empower agriculture professionals with the most accurate, science-based tools to help make the best decisions for businesses, their growers, and the Earth. 

We know that it’s not just the soil or the crop that you make a decision based on – it’s the complex relationship between your crops, the environment, nutrients, and more. That’s why we help you harmonize and standardize all of your agronomic data to turn it into actionable insights. 

That’s the core of INM. It is balancing crop needs, the environment, nutrients, productivity, and profitability to deliver on the needs of today and tomorrow. Integrated nutrient management for sustainable agriculture and Agmatix are a winning combination for building lasting relationships with growers, caring for the Earth, and tackling the challenges of 21st-century agriculture. 

Compelling Reasons Why Farmers do On-Farm Experiments 

For over two centuries and around the world, farmers have been conducting on-farm experiments. This has allowed the translation of experimental research into real-world agronomic practices at the individual farm level. It has also connected farmers, researchers, and other agriculture industry professionals in mutually beneficial collaborations. 

On-farm experiments, while not formalized, are taking place on an estimated 30,000 farms around the world. That means on-farm experimentation today is driven by a diverse set of goals, approaches, locations, and sociotechnical ecosystems.  

The on-farm experiment process involves close collaboration with farmers to change a management value, observe the outcome, and discuss that outcome with the major goal of driving evidence-based learning and decision-making. Farmers bring deep knowledge of local production practices and experimental mentality. But effective integration between science-based and farmer-based knowledge can be a challenge. 

Farmers say what they need to improve their business is information that’s specific to their field and location, not just within their state or region . Agriculture research today is often reflective of best practices that are generalized across a wide range of farms rather than the specific challenges and considerations of one individual farm. This has been driven by reduced funding for local research

So, many farmers have turned to on-farm experimentation to gather information on their own fields to supplement academic or industry-sponsored research. Digital agriculture has the opportunity to unlock more value from these on-farm experiments. Standardized data collection and easy data analysis can increase the ease of conducting on-farm experiments and using the outcomes to make decisions. Field research software can support this. 

In fact, involving an agricultural research management software or experiment monitoring tool from the beginning of the trial has major advantages. Setting up the trial for replication and randomization enables sound decisions from on-farm experimentation. This is because it allows the data to be statistically verified. Digital tools can help farmers design the trial, and GPS guidance, yield maps, and aerial imagery can help pinpoint and execute the trial. 

The ROI with On-Farm Experiments

The reasons for doing on-farm experimentation may be specific to each farmer. For example, one grower might use the trials to understand yield gain or loss on a given production practice. Another points to the learnings from both successes and failures. And yet another uses trials to determine what inputs are absolutely necessary – and which ones can be cut. Amongst all of the farmers interviewed on their reasons for doing on-farm experiments, profitability was a common theme. Because of this, we’ve highlighted some of the main return on investment opportunities associated with on farm experiments. 

Understanding locally-relevant knowledge

Variability is common within a single field – imagine how varied growing conditions and climate can be across a county or even an entire state. For farmers, understanding the impact of a production practice in their specific growing conditions and climate is critical. 

Farmer-led on-farm experiments typically have more replications than those of agricultural scientists. Coupled with the specific soil types and weather conditions that are of interest, there’s a particular power in the vast, local data collected from on-farm experimentation. 

While these experiments may be less precise, they are an excellent complement to scientist-led research. A farmer’s local knowledge combined with a researcher’s product-specific knowledge work well together to conduct these experiments and ensure the outcomes will be relevant and impactful. 

Test research questions for the broader benefit 

Understanding and evaluating new products or practices on a small scale can help minimize the initial risk. Farmers can assess early, local, and small-scale results before going all-in and adopting something new. 

Farmers can use the outcomes of on-farm experimentation to fuel profitability-focused decisions and understand yield impact on their farms. These outcomes can also apply to other local farms – and have the potential to improve profitability and crop yield for others, too. 

Test questions also open the door to technology adoption. When new products and technologies arrive on the farm, growers have to explore how they work in their environment to determine the return on investment. New technology is also available to aid farmers in their decision-making, such as agricultural research management software. Not only is this technology being tested through on farm experimentation, but it also unlocks additional potential for on-farm experiments to be doubly powerful. 

Financial gains 

On-farm experimentation directly provides data to help farmers make decisions that impact the bottom line. Whether it’s improving crop yields and maximizing production, reducing the number of inputs like fertilizer that are needed to cut costs, or reviewing overall profitability, financial gains are possible from on-farm experimentation. 

On-farm experiments also reduce the risk of wasted time and money on new products or production practices. By understanding how that specific product or practice performs on a farmer’s own land, the chances of wasted time and money are reduced – even if the product or practice doesn’t work out.

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On-Farm Experiments with Agmatix

At Agmatix, we support agriculture professionals globally to overcome obstacles in the journey to grow sustainable food production and quality. One of the ways we walk beside producers in this journey is through the tools we provide to assist with experimental collaboration. 

Agmatix mobile is an easy data collector for agronomic trials to address one of the most critical aspects of any experiment. This field research software enables timely reporting, minimized errors, and secure processes for storing and aggregating the data for analysis. Farmers can see the true value of the data they collect from field trials, and work collaboratively with others through easy sharing to maximize its impact. 

The Agmatix field research app also allows farmers to leverage legacy data from published research or from local trials conducted near them. Data standardization helps unearth insights from multiple data sets. And pre-built analytics speed up the process of transforming big data into impactful insights. 

Tools like the Agmatix mobile application are designed to make OFEs easy. Experiment monitoring tools with intuitive user interfaces allow farmers to check in on their trials and manage them throughout the growing season. Experiencing results in real-time is possible, too! 

Planning on-farm experiments can be challenging, too. Trials must be designed with treatment combinations that are flexible but keep trial outcome integrity at the forefront. Agmatix’s Agronomic Trial Management mobile app has customizable treatment combinations and trial layouts. With the app, it’s easy to visualize the trial design and layout and create data collection forms based on the parameters needed for each trial.

On-farm experiment tools have incredible power to support farmers in conducting on-farm experiments. From supporting data collection and standardization to enabling fast and easy analysis, farmers can truly experience the return on investment of their on-farm experimentation through digital tools. Agmatix is proud to offer on-farm experiment platform that helps farmers and their collaborators with these important trials. 

Unearthing Potential in Your Soil with Agmatix

There’s more to soil than what meets the eye. As the basis for life on Earth, soil is a big deal! 

Soil health is part of the bedrock of agriculture. In the last decade, interest in soil health has increased as a focus on sustainability and the benefits of healthy soils have become more mainstream. In honor of Soil Health Day, we’re breaking down the facts about soil, soil health, taking care of soil, and making sure it’s healthy for generations to come. 

What is soil made of? 

As every farmer knows, what covers the Earth and grows crops isn’t ‘just dirt.’ But what is soil made up of? While it may look like a single, dusty brown substance, soil is a combination of minerals, organic matter, living organisms, gas, and water. These give soil unique, location-dependent characteristics. 

Soil has been studied since the 1800s when soil scientists began looking into what soil is made of. Scientists have classified soil horizons, or layers within the soil, as well as soil age, soil minerals, and more! Soils are diverse due to differing parent materials and formation conditions. 

Major contributions were made by Hans Jenny introducing the CLORPT concept: soil formation is affected by Climate (CL), Organisms (O), Relief (R), Parent material (P), and Time (T). This conceptual model for understanding soil geography and geomorphology has had many impacts on soil science. It’s been a global foundation for understanding soils as a function of combined environmental factors.

Around the world, soil reflects various factors, including geologic events, organisms, climate, topography, and time. These five factors impact soil from the surface to its lowest depths. A change in one of the five soil forming factors results in “soil genesis”, creating a new soil. 

Geologic Events

Soil parent material is a result of geologic events, such as volcanic eruptions or glaciers. Volcanic ash is a lightweight parent material with high water-holding capacity and compaction susceptibility. Glaciers have ground up rocks and pushed glacial till to the soil surface, generating a different parent material entirely. And in swampy areas, peat is a common soil parent material generated from decaying plants and animals. 


All living plants and animals can impact soil formation. Soil horizons often reflect the types of plants that grow on a site, with residue like needles, twigs, and roots incorporated into the soil. Organisms in the soil break these plant residues down. Microorganisms are present in all soils, though the types of microorganisms will depend on the plants that are present on the site. Other organisms, like worms, voles, and moles, impact the soil by creating channels in the soil or mixing it, which helps move water and air throughout the soil. 

Climate and soil

Climate, including temperature and annual precipitation, can have massive impacts on soil formation. Wetter climate can support richer vegetation, which decomposes and in time affects soil formation and its characteristics. Too much water in soil can reduce soil air, and impact what types of plants can grow on that site. Documenting annual precipitation and average soil temperature is important for understanding the climate of a given site. 


Topography refers to the type of landscape the soil is in. Landscape location includes elevation, shape, and compass direction. All of these factors change soil drainage, runoff, deposition, and erosion. For example, south-facing slopes dry out faster and are warmer from high solar heat, which speeds up chemical reactions and water evaporation. This influences soil genesis. 


Soil landscapes are continuously building and degrading throughout time. Soils can be young or old. Climate can impact how quickly soils form; in hot, wet climates, soil horizons form more quickly than in cold, dry environments. Young soils have little horizon development, while older soils have many well-defined soil horizons. 

Understanding soil characteristics and what it is made of is important because of all the ways soil contributes to life on Earth. Soil plays a part in regulating water, sustaining plant life, and cycling nutrients. Soils provide nutrients and water for most of the plant life on Earth. 

They also filter pollutants and transform nutrients into biologically available forms that are prevented from leaching. All in all, soil contributes ecosystem services that microorganisms, plants, animals, and the environment all depend on. 

Is Your Soil Healthy? 

Because soil is a living natural resource, it’s possible for it to be in different states of health. Soil health is the “continued capacity of soil to function as a vital living ecosystem that sustains plants, animals, and humans,” according to the U.S. Department of Agriculture’s Natural Resources Conservation Service

In agriculture, soil health is of particular importance. Agriculture fundamentals require plant and animal life to be sustained. Soil’s ability to regulate water, filter pollutants, and stabilize and support plant roots are critical puzzle pieces to growing plants and raising animals for agricultural purposes. 

And for agriculture to be productive, plants need nutrients from the soil to grow and produce high-quality food. Because of this, soil fertility and soil productivity are of high importance. Nutrients like carbon, nitrogen, and phosphorus are cycled, stored, and transformed in the soil, fueling plant growth and productivity. 

When soil health is degraded, it can’t complete these critical functions. In short, there are many benefits of soil health that have importance in agriculture!

It’s possible for stewards of the land to protect and restore soil health, guided by soil health principles. Soil health principles include maximizing the presence of living roots, minimizing disturbance, maximizing soil cover, and maximizing biodiversity. 

Farmers can use soil health principles to focus on improving soil health. Some ways to improve soil productivity include composting, cover crops, crop rotation, and soil assessments. 


Composting organic material can drive soil health improvement. It can supply organic nutrients which can substitute synthetic fertilizer and it can build up the soil organic mater, which helps stabilize aggregate stability and help the soil withstand soil erosion and gullying. Composting can promote a slow release of nitrogen, too. 

Cover Crops

Cover crops, like rye or crimson clover legumes, are grown to protect the soil during times it is normally fallow. Cover crops are one of many ways to improve soil productivity and restore soil health. There are many benefits to cover cropping, including increasing organic matter, suppressing weeds, reducing erosion, managing compaction and soil structure, and increasing water infiltration. Cover crops do a great job of addressing all four soil health principles!

Crop Rotation

Rotating planted crops has many benefits for yield, drought tolerance, and plant disease. Crops with different rooting depths can be used in crop rotation to improve soil structure. Cover crops can be used in crop rotation to increase diversity, improve organic matter, and prevent erosion. 

Soil Assessments

Collecting data to understand the current status of soil is a critical step to determining the best course of action to protect or restore it. Soil testing and field observations can help determine the health of the soil, including physical and biological properties. 

Automate Plant Nutrition 

Because of the importance of soil health in agriculture, taking active steps towards soil health improvement is important. Beyond production practices like cover crops and composting, farmers can find ways to improve soil productivity by streamlining plant nutrition with soil health and sustainability in mind.

Soil may not naturally have the right composition or rate of nutrients for a given crop. Or, the nutrients may not be in a plant-available form. In these situations, farmers must balance applying the right type and rate of fertilizers, because over-applying can impact soil health and negatively impact the environment. 

Soil health decreases when you underapply nutrients, and soil organic matter gets depleted. Using an adaptive approach to nutrient management and regular soil testing enables tracking of nutrient levels. Armed with this knowledge, it’s possible to re-supply adequate nutrients as needed, either through manure or synthetic fertilizers. 

Adaptive approaches to nutrient management take into consideration the current state of the field and its variability. Within a field, variability in soil texture, organic matter, nutrients, fertility, compaction, soil depth, and drainage is present. Planning for all of these factors is difficult, if not impossible, with a one-size-fits-all solution. A decision support system tool, like Agmatix’s Digital Crop Advisor, makes it easy to adopt an adaptive approach to nutrient management.

Agmatix’s Digital Crop Advisor

Digital Crop Advisor is a data-driven decision support system that automates plans and makes the best of crop nutrients for a specific site. Because of the importance of soil productivity and soil fertility, a tool like Digital Crop Advisor can help assess and meet a field’s nutritional demands with environmental sustainability and soil in mind. With Digital Crop Advisor, it’s easy to meet crop nutrition needs. 

The Digital Crop Advisor map interface uses two types of satellite imagery – Sentinel-2 and Landsat 8 – with a 5-day revisit time frame to ensure accuracy. Site-specific recommendations are created using various parameters that can be customized. Yield uptake, previous crop performance, removal rate, soil characteristics, and environmental impact are just a few of the possible parameters that can build a precise, customized, optimized plan. 

Digital Crop Advisor also connects to soil analyses to enable integrated crop nutrient management. This allows adjustments to the nutrition plan to be made as needed. Lab analysis results can be used in-season and pre-season to adjust for seasonal nutritional demand. 

In a specific sustainability section, a detailed carbon footprint assessment helps farmers understand the impact of a specific nutritional plan recommendation on the environment. The sustainability section also provides a benchmark for future recommendations. Farmers can continue to improve production practices and enhance inputs with sustainability in mind. Ultimately, meeting nutritional needs with a low environmental impact leads to high yields and productive crops that enable continued growth well into the future. 

Ensuring Your Soil’s Future

The future of the world’s food production depends upon the health and productivity of agricultural soils. Farmers have a big job in protecting and restoring soil health while feeding a growing, hungry world. 

With a global population projected to reach close to 10 billion by 2050 and the challenges of a changing climate, food security relies on the capability of current soils under production to continue to produce well into the future. 

At Agmatix, we support agriculture professionals in improving sustainable food production. Food production is both impacted by and impacts soil health, and Agmatix is dedicated to providing data and decision support for farmers and industry professionals as they navigate sustainable food production and crop nutrition. With tools like Digital Crop Advisor, Agmatix is helping pave the way to a sustainable, healthy soil future. 

If You Ate Today, Thank a Farmer

Thanksgiving originated as a day to give thanks for the harvest and the preceding year. It’s celebrated in many countries around the world, including the United States, Canada, Libera, and Germany. 

When it comes to gratitude, there is one group that stands out as particularly deserving of thanks: farmers. At Agmatix, we want to extend a special thanks to farmers this Thanksgiving for all they do, and share some of the tools we’ve developed as an agro-informatics company to help them do what they do best. 

Brought to you by Farmers

Roughly 2 million farms, of an average 445 acres, exist in the United States today. That number was once over triple at its peak in 1935 when agriculture was a labor-intensive endeavor that required many small, diverse farms. Between 1935 and 1970, the number of U.S. farms dropped rapidly as non-farm employment options and on-farm productivity both increased. Today, only 1.4% of the U.S. population is actively involved in farming. 

In more recent years, the number of farms has continued to decline, though more gradually. The amount of land and labor used in farming has also decreased. However, total farm output has nearly tripled from 1948 to 2019. Thanks to technological developments, a U.S farm feeds 166 people annually – both domestically and abroad. Those developments have included genetic improvements, chemical and equipment innovations, and farm management. 

It’s not just large farms that meaningfully contribute to the world’s food supply. A 2021 FAO report noted that smallholder farmers who farm less than 2 hectares produced an estimated 35% of the world’s food on 12% of all agricultural land. Smallholder farmer impact varies based on country, with some countries like China having smallholder producers responsible for 80% of contributions to the food supply. 

Around the world, there are an estimated 570 million farms – 9 out of 10 of which are family farms. Those family farms, of all sizes, produced around 80% of the world’s food. 

Regardless of farm size, location, or crop production, there’s one thing that farmers all have in common: they’ve got many, diverse responsibilities. It takes a lot to nurture a crop from seed to harvest, and farmers have to be experts in crop production. And despite technological advancements, much of crop production is still dependent on some degree of manual labor. 

Farmers have to deeply understand inputs like seeds, fertilizers, herbicides, fungicides, and insecticide options. They have to operate, maintain, and buy equipment. They work with landlords and banks and government agencies. Day-to-day operation requires logistical prowess and management skills. And understanding the crop and commodity markets to make important contracting and sales decisions requires expertise in that area, too. It takes a lot of knowledge to be a farmer! 

With everything on farmers’ plates as they try to put food on America’s plate, there’s definitely an opportunity to lighten their load. Agmatix has designed tools with farmers in mind – to make the tough decisions a little easier. 

Agmatix Tools for the farmer

Farmers have a lot of production aspects to manage and decisions to make. There are a few Agmatix tools that can make handling agronomic trials, decision-making, and data management easier. 

Agronomic Trial Management 

Many farmers use on-farm experiments to explore how different products and production practices impact yield or product quality on their land. The data and insights from these on-farm experiments can be powerful tools to support decision-making toward increased yield, profitability, and sustainability. But managing the trials and subsequent data can be a challenge. 

Agmatix makes planning on-farm experiments simple with intuitive design methodologies and multiple treatment combinations. With the drag-and-drop your trial layout directly on a map, it’s even easier to configure an on-farm experiment for success. While the on-farm experiment is ongoing, the extended mobile app capabilities keep farmers connected to the trial – even providing status updates to keep the experiment on track. Collecting data is easy, and can be standardized with legacy data for maximum impact. And if you’re interested in trials completed or ongoing near you, we can connect you with local trial coordinators to expand the available research knowledge of your “virtual toolbox”.

Digital Crop Advisor

Making crop input decisions can be challenging, even with the help of an agronomist. With Digital Crop Advisor, farmers can easily identify the best nutrient protocol to maximize crop yield and quality, all while minimizing environmental impact. Farmers can create plans for up to 12 nutrients across 150 different crops to unleash their full potential. And all of these capabilities exist in a user-friendly interface that allows farmers to dig into performance and analyze results in real time. 

Open Databases

The Global Crop Nutrient Open Database was created in collaboration with the Consortium of Precision Crop Nutrition (CPCN), the International Fertilizer Association, and other partners. The database provides important information to improve plant nutrition plans. It contains data on nutrient content, residues, crop yields, and other related data. It allows farmers to look at production and environmental factors that impact nutrient concentration to understand the total nutrients removed from the field when the crop is harvested.  

The Global Crop Nutrient Removal Database can fuel crop management decisions as farmers assess crop nutrient removal rates and trends of nutrient demand. They can make educated decisions about nutrient application to supplement soil nutrients. And the database is accessible to both farmers and researchers to ensure open science and collaboration. 

The Nutrient Omission Trial Database supports site-specific recommendations that optimize nutrient management. Using this data, farmers can compare crop nutrient requirements and plans. The database is sensitive to soil fertility variations and takes site-specific conditions into consideration, so farmers can confidently understand trends in nutrient use efficiency in a given geography. 

The database is a collaboration between Agmatix, the African Plant Nutrition Institute, the International Fertilizer Association, and Innovative Solutions for Design Agriculture. It brings legacy nutrient omission research data into a single, open dataset. And the data is standardized and harmonized to improve collaboration. The data is even enriched with geospatial information on soils, crops, weather, and more. 

Hats off to Farmers

As U.S. President Dwight Eisenhower once said, “Farming looks mighty easy when your plow is a pencil and you’re a thousand miles from a cornfield.” Farming can be risky, as the markets and weather are outside a farmer’s control. What works on paper might fail in the field, and Mother Nature might throw a curveball at any time.

At Agmatix, we know farming isn’t a 9 to 5 job for 40 hours a week. Farmers work in acres, not hours – and work until the job is done. They wear a lot of hats on the farm and need to be experts in many areas. Regardless of rain, snow, or sunshine, holidays or weekends, farmers can be found working hard to reap what they sow. That’s why we’re proud to serve farmers and support the time-honored work they do. 

Farmers produce the food, fuel, and fiber needed to keep the world running. So this Thanksgiving, don’t forget to pause and thank the farmer that helped your holiday dinner make it to the table. 

Top 5 2023 Agriculture Trends to Watch

The agricultural industry is always growing and progressing. Growing food, fuel, and fiber look much different today than it did hundreds of years ago. Mechanization changed agriculture’s reliance on human labor and horsepower. The Green Revolution harnessed selective breeding allowing more grain to be produced per acre. And today, technology like big data and artificial intelligence is driving another wave of change to improve the way we farm.

In 2023, keep an eye out for trends in agriculture that represent familiar challenges and new technologies. With USDA agricultural projections, the adoption and implementation of artificial intelligence (AI) for furthering crop optimization, and capabilities for remote big data analysis, we’ll outline some of the biggest upcoming agroinformatics trends. Then, we’ll share how Agmatix – a cutting-edge agroinformatics company – can help make sure you’re on top of the changing industry. 

1. Feeding a Growing World 

By 2050, the Food and Agriculture Organization estimates we will need to produce 60% more food to feed a world population reaching nearly 10 billion. Even if we hit that mark, 300 million people will still be grappling with food scarcity.

Developing countries will have a growing role in the global economy and food demand. Today, countries like the Philippines and Colombia are setting records for U.S. exports. In 2023, developing countries will continue to account for most of the growth in U.S. agricultural exports. 

Global crop production and trade continue to be variable, driven by factors like technological environments and the geopolitical climate. The USDA Foreign Agriculture Service estimates that by 2023, global rice consumption will be up by 7M tons to surpass 518M tons. Due to inflation, food prices are expected to rise between 3 and 4 percent.

The US Farm Service Agency also indicated that for 2023, there would be fewer acres dedicated to corn production in the United States – a decrease of 1.2M acres. This means that there will be a greater need for farmers to produce more within the land that they have to meet the needs for ethanol, animal feed, food, and fiber production with the growing global population.

The agriculture industry has been severely impacted by extreme weather events, COVID-19 supply chain disruptions, and worldwide economic concerns, as reported by the World Agricultural Supply and Demand Estimates in 2022. All of these factors, and more, have the potential to shift the reality of 2023 from these projected outlooks.  

2. Artificial Intelligence  

As technology adoption grows, the digital age in croplands continues to thrive! From measuring soil nutrient levels to monitoring irrigation amounts and using droney imagery to map crop fields and estimate disease presence, artificial intelligence (AI) will become a constant presence in agriculture productions of all sizes. 

According to BI Intelligence Research, global spending on smart technology and connected systems in the ag space is projected to triple in revenue by 2050. That includes AI and machine learning. AI spending alone is predicted to grow at a compound annual growth rate of 25.5% between 2020 and 2026, eventually reaching $4 billion. 

Synthetic data is often used to validate AI models. Synthetic data is based on real-world data and created by a model that uses the parameters of real-world datasets. A “digital twin” with synthetic data in a system that emulates real life can be particularly helpful in agriculture, where variables like soil types and weather conditions must be understood for real-world applications. Synthetic data is a powerful tool – so much so that Gartner predicts synthetic data will outpace real data in AI models by 2030. Synthetic data and AI will be trends that can be operationalized in agriculture in 2023 and beyond!

3. Precision Agriculture 

Precision agriculture harnesses smart, connected technology systems to improve grower outcomes. Growers can save time, money, and resources – which are all at a premium in today’s world – with tools that support crop monitoring and targeted crop nutrition plans. 2023 trends in digital agriculture will include exciting updates in the precision ag space. 

Agmatix’s Digital Crop Advisor is a data-driven decision support system that connects fields, farmers, and agronomists. Armed with seamless crop nutrition optimization plans, sustainability KPI monitoring, and data from over 150 different crops, farmers can make the best decisions for their fields and the environment. 

And in 2023, using precision agtech tools for precise fertilizer application will be more important than ever. At the start of the 2023 season, farmers will face far higher fertilizer costs. Nitrogen prices, driven by corn prices, natural gas prices, and geopolitical events, are expected to be higher than just a year earlier. Fertilizer costs have increased the most of any input in 2022. 

4. Big Data

The Internet of Things (IoT) and the copious amounts of data associated with sensors and equipment are driving forces in the agricultural revolution. While agriculture might not be what immediately comes to mind when you think of the Internet of Things (IoT), it’s a driving force in the agricultural revolution. Generally speaking, IoT represents billions of smart devices with chips and sensors that are connected to the internet. 

Smart agriculture systems that use IoT collect massive amounts of data. For example, networks of connected sensors, devices, and infrastructure create digital twins of the crop and field. This develops machine learning to further applications of technology in agriculture. 

Remote data analysis is becoming more common, too. In combination with AI, IoT-driven data analysis can provide insight into complex things like crop performance and climate patterns. Because crop performance is dependent on so many factors, data analysis can help farmers, agronomists and industry professionals better understand the impacts of technologies, production practices, or even the changing climate. 

In order to support big data in agriculture, larger compute-and-store architecture is needed for real-time data analyses. One example of this need is field trials – which create a lot of data. The potential for field trials to drive decision-making is only unlocked when the various datasets collected can be analyzed and turned into actionable insights.

Big data analytics can be the key to supporting big data in agriculture, especially in real-time. For data-driven decisions, Agmatix’s Agronomic Trial Management solution allows collected data to be standardized. This allows data to be evaluated, compared, and protected from potential loss. This powerful capability is housed within a user-friendly interface to support farmers and researchers in their analytics. 

Another aspect of big data is the databases in which data is stored. Open databases with standardized data that can be shared across different experts and stakeholders allow for maximum collaboration. Innovation and new ideas in agriculture are possible when open science is supported and researchers around the world can access high-quality data to support their work. Agmatix is leading the way in this area with the Nutrient Omission Trial Database and the Global Crop Nutrient Removal Database. 

5. Sustainability

Sustainability isn’t a new trend or topic in 2023, but it’s a safe bet that companies will double down on their efforts and they’ll need to quantify their impact on sustainability. The agriculture industry will have similar opportunities to engage in sustainability efforts with renewed vigor. 

Agmatix is committed to helping agriculture professionals improve sustainable practices in food production. Managing both crop yield and quality while addressing sustainable farming will be key. Digital Crop Advisor monitors sustainability KPIs in recommended crop nutrition and fertilization plans to estimate the carbon footprint and nitrogen leaching. This provides farmers and agronomy professionals with the information they need to choose the most sustainable crop nutrition plans. 

Along with positively impacting the environment, financial benefits of environmental sustainability also exist. 

For US producers, the USDA’s Natural Resources Conservation Service offers a variety of financial resources to support conservation and resource sustainability. Both technical assistance and financial support are available for improving air quality, conserved ground and surface water, soil health, improved or created wildlife habitat, and more. 

Carbon markets are one example of a new financial consideration for crop producers. While the U.S. carbon market is still developing, there is increasing interest in pricing carbon and evaluating offsets to drive farmer behavior. 

Agmatix Helps You Stay On Top of Trends in Agriculture 2023

Staying abreast of all the changes in the agriculture industry can be a challenge. But with pressures from a changing climate and growing population, adapting is necessary. Luckily, Agmatix has a hand in all of 2023’s major digital agriculture trends. As a single source for sustainability based on crop models and big data, Agmatix makes it easy to stay on top of agtech trends in 2023.  

As agriculture changes and trends influence priorities, quickly understanding the impact of new technologies or production practices is critical. But it’s difficult to isolate the impact of a given factor on crop yield or quality. Agmatix has solutions available to create crop models that predict plant growth and development based on crop management practices and the environment in which the crop is grown. These models can be used to assess future impacts of climate change, too!

Agmatix also connects precision ag, big data, and sustainability in the nutrient management space. With tools like Digital Crop Advisor, Agmatix makes it easy to make data-based, site-specific management and optimization decisions for over 150 different crops. And sustainability stays at the forefront with KPI monitoring. An agriculture field trial data tool has a lot of power to support profitable, sustainable decision-making. 

All of these tools are based on big data collection and agriculture data enrichment. Agmatix helps turn agronomic big data into powerful insights that can change the way we farm. Our platform ingests and harmonizes datasets – including legacy trial data. Turning that data into actionable insights is simple with statistical analysis that requires no code. And collaboration with big data is easy with standardized data through the GUARDS ontologies

Agmatix remains forward-looking when it comes to data and technology. With over 670 million data points and 53 million values of professional observation, it’s possible for Agmatix to generate synthetic data to support digital twins. Digital twins – where a computer uses real-world data to maintain statistic correlations – have enormous potential to emulate real life in agriculture. 

It would be possible to create a digital twin of a field trial to understand which variables are needed for the trial to be successful in the real world. Knowing the necessary soil type or weather conditions can drive meaningful results quickly, and at scale. Digital twins could also be used to fill in gaps in real-world datasets. Synthetic data based on statistical models can complete the picture if a remote sensor fails or equipment errors leave data missing. 

Agmatix is staying on top of agroinformatics trends by building on a foundation of big data and precision agriculture. Feeding a growing world while caring for the soil, water, and climate that sustains agriculture will be a challenge. In 2023 and beyond, Agmatix is making cutting-edge technology available to grow data for impact across the industry. 

5 Tips for Designing a Successful On-Farm Field Trial

Field trials are woven into the history and future of agriculture. They’ve been heavily used in formal plant breeding for the advancement of agricultural practices, products, and ideas.

Equipped with the tools to gather and interpret field trial data, you can now use agricultural field trials as a powerful way to determine what inputs and agronomic practices work best on your land. And you don’t need to be a research and development crop researcher or data scientist to glean insights from these trials. 

There are five key steps to use this scientific practice as an effective on-farm, boots-on-the-ground practice: identify the why, design the trial, gather data, interpret results, and draw conclusions. With these five steps, you can be better equipped to conduct a well-designed on-field experiment

1. Identify the “why”

Beginning with the end in mind is critical for successful agricultural field trial design. You need to identify the purpose of your on-field experiment and define the research question you want to answer. What do you want to learn from your agricultural experiment?

Good field research questions can be answered with a “yes” or “no” and will directly impact your farming operation or bottom line. Answering these questions will give you the information you need to make decisions about your agronomic practices, which inputs your crop needs, and how you can increase yield, reduce cost, and improve sustainability. 

A few examples of good research questions could be: 

“Would applying fungicide in-furrow in corn at planting increase yield?” 

“Does corn variety X yield higher than corn variety Y in well-drained soils?” 

“Does the use of a bio-stimulant increase corn yield?” 

The research question will then help you determine what controls or treatments are needed. 

The treatment group receives the change that you want to see the results of – such as a drought-resistant variety, an earlier planting date, or a new insecticide. 

The control or check group is identical in all ways to the treatment group except they don’t receive the treatment. The control is used to compare the results of the treatment. Control plots and treatment plots together are referred to as a block. 

The research question you select should provide a clear line of sight to the equipment and resources needed to complete the trial. As you plan out the research question, think through how the results can be measured, if the available test site is appropriate for the research question, and how the field history might impact the outcome of the study. 

Keep in mind that field trials can be conducted on a single farm or across many locations. 

2. Design the trial 

Any on-farm experiment requires a good field research design. While few fields out there fit the “flat and square” description, even slight variations in slope, fertility, and soil type can impact the integrity of field research. 

To control for field variability, field trial design should account for variation. Fields should be sectioned according to field characteristics. Using replication and randomization in the on-farm field trial design can reduce result bias and account for field variability as well. 

Replication means repeating field trial treatment blocks of the control or check and the treatment, often four to six times, across the field. This provides a large quantity of data. But, it may not minimize result bias, depending on the field characteristics. For example, a field whose northern end consistently yields higher means the northernmost treatment in each block would always yield higher. 

Randomization can be used in combination with replication to overcome field variability. The treatment blocks are placed randomly throughout the field as opposed to in a pattern, which removes any preference for one treatment over another. 

Research designs set the on-farm field trial up for success, both in execution and in data analysis. Research designs should include both replication and repeatability. Conditions within blocks should be similar but can differ from block to block. 

Some common agricultural field trial designs include paired comparisons, randomized complete block designs, and split-plot designs. 

A paired comparison is a field trial design for comparing any pair of treatments, such as two different fertilizer rates or crop varieties. Blocks include one plot of each treatment, placed randomly within the block. The block is replicated across the field, typically four to six times. A paired comparison is a type of randomized block design, but because it only involves one treatment and one control, statistical analysis of the results is more simple. 

For a comparison of three or more treatments, a randomized complete block design is a good choice. It involves a block that includes all treatments and an untreated check in a randomized order within the block. The block is repeated at least four times across the field. 

Interactions between treatments can be studied through a split-plot design, where main treatments have sub-treatments applied to them. Split-plot design can also be used when one of the treatments requires additional replication. This field study research design requires a larger area and additional management due to its complexity.

3. Gather data

Data collection is an essential part of your on-farm experiment. Take note of what data you need to collect before you begin your on-farm research.

You may already record things like planting, application, harvest dates, varieties and population(s) planted, and moisture.r Collecting your normal data in a consistent manner as well as capturing additional crop condition and growth data is critical. Data collected could include notes or photographs. Information such as node or pod counts, pest pressure, or storm damage will help you better interpret the study results after the crop is harvested. 

Yield data is a vital dataset to capture for your on-field experiment. Ensure weight is measured from a calibrated scale, and moisture and test weight are also captured, if applicable. Consider capturing data from the center rows of each plot to minimize the impact of potential treatment drift. 

Your on-farm research plan should include data management and storage processes. Cloud-based technologies and telematics make data collection and storage automatic, reducing the opportunity for error and creating efficiency. 

4. Analyze and Interpret Experiment Results 

Interpreting data collected during field trials can feel overwhelming. But analysis is what makes data actionable, and it requires going beyond a simple comparison of treatment averages.

Statistical analysis helps determine if there’s a significant difference between treatments – meaning the results aren’t due to chance or variability within the field. 

When an experimental is designed for statistical analysis – such as one of the agricultural field trial designs above – the Least Significant Difference (LSD) can be used to determine whether the results are likely to occur again in the future because they are due to the treatment. The LSD is based on a probability level that indicates how certain you can be that you’re correct. If the averages of the two different treatments differ by more than the LSD value, you can be confident that the result will likely occur again in the future.

You don’t have to be a statistician to have confidence in your on-field experiment design and results. Today, there are powerful agronomic tools and software available at your fingertips to streamline this process. Using technology to manage data, including storing it and sharing it with farm advisors, can also make the interpretation of field trial results simple. 

5. Draw Conclusions and Determine What’s Next 

Think back on the initial research question. What conclusions can you draw from your agricultural experiment? Based on your findings, you might decide to change production practices or that it just didn’t pencil out. Either way, the results are valuable to understand field performance and management outcomes. 

You might be ready to make a decision for next year based on what you found. Or, you might still have questions or doubts. To build confidence, you can conduct the same on-farm field study over multiple seasons or in different fields to ensure the results weren’t tied to that year or that location. 

It’s also worth thinking about how to enrich your dataset. Is there a neighbor you could partner with to expand the trial? What about an aggregated, legacy dataset that you could compare your results to? Knowing if the results are repeatable both on your farm and across a broader geography can be helpful when deciding to implement a new practice as a result of an on-field experiment. 

You may be interested in:
Trial and Error: Navigating Agricultural Trials with Biologicals
CROs Can Count on Agronomic Data Analytics Tools
Agronomic Field Trial Compliance and Reporting with Advanced Tools

Agronomic Field Trial Design and Management Made Easy with Agmatix

The five steps for field trial success are building blocks for better decision-making on the farm. A well-conducted agriculture experiment can unlock yield potential and build confidence in the return on investment of new production practices. 

But, the process doesn’t have to be difficult. Agmatix’s holistic field trial software is a user-friendly platform designed to help you scientifically plan and manage on-field experiments. You can design your trial on-map with hundreds of treatment combinations. You can set up status updates for your field trial and easily communicate with those involved in the trial. 

Once your trial is complete, data collection for agronomic trials makes it easy to use big data to create value for your farm through operationalizing insights. You can standardize legacy data or combine agronomic data to dig deeper into information that was once difficult to piece together. With the whole picture in mind, field data management can take your on-farm field trials to the next level. You can be confident in the next best step to farm for the future. 

Agmatix’s Carbon Footprint Optimizer

Every choice and every action has an impact on carbon footprint. Unlike footprints in the sand, the results of our actions don’t just fade away with the next big wave to wash ashore. 

While that sounds like a big responsibility, it’s also a great opportunity to be more aware of carbon-intensive activities and actively work to reduce greenhouse gas emissions. 

What is carbon footprint?

Carbon footprint is defined as the total amount of greenhouse gases generated by a person, organization, action, or product. Common greenhouse gases include carbon dioxide, methane, and nitrous oxide. 

Globally, the average person’s carbon footprint is 4 tons. A person’s carbon footprint is impacted by how they travel, the electricity and water they use in their home, and even what they eat. 

The consequences of high carbon footprints have already taken their toll on the global climate. The Earth is now over a degree celsius warmer than it was in the 1800s. 

Limiting temperature rise to less than one and a half degrees celsius would limit the most challenging climate impacts, but globally, this is out of reach based on current emissions levels. Carbon dioxide emissions, if left unmitigated, could increase the global temperature by as much as 4.4 degrees Celsius by the end of this century. 

Carbon Footprint in Agriculture

People aren’t the only ones who have measurable carbon footprints. Products, businesses, and even industries can measure their carbon footprints – and agriculture is no different. 

It’s estimated that US agriculture emitted 669.5 million metric tons of carbon dioxide in 2020, which equates to 11.2% of the total GHG emissions in the US (compared to industrial, transportation, commercial, and residential categories). That’s the equivalent carbon footprint of nearly 167.4 million global citizens. 

Globally, agriculture, forestry, and land use change contribute nearly a quarter of all Greenhouse Gas Emissions. 

From production to food supply chains, an estimated 31% of human-caused global greenhouse gas emissions come from the global agri-food system. That’s approximately 16.5 billion tonnes of greenhouse gas emissions, primarily stemming from deforestation and livestock manure. 

Five footprint-influencing crop production processes include crop production products, fertilizer production, fertilizer application, energy and fuels, and other inputs such as seed or water. To better understand the impact of these processes, CropLife International compared them across their main production regions to determine their overall carbon footprint. 

The results show that different crops have vastly different ratios of carbon footprint by the crop production process. For example, energy and fuels contribute the most to cotton’s carbon footprint, but fertilizer production has the largest impact on the carbon footprint of maize and wheat. 

Across cotton, maize, rice, soybeans, and wheat, crop production products had the lowest percentage contribution to the crop’s carbon footprint. These products increase the efficiency of other inputs and production practices, such as fertilizer or tillage, because they protect yield. 

They also reduce the need for in-field activities that have high greenhouse gas emissions. In some cases, crop production products have a net positive contribution to carbon footprint. 

By contrast, fertilizer production and application processes combined make up the majority of every crop’s carbon footprint. Variances in fertilizer inputs across global geographies and production regions have a large impact on the carbon footprint of the same crop if grown in different places with different fertilizer sources and production practices. Reducing fertilizer carbon footprint is crucial for lowering agriculture’s overall carbon footprint. 

Different production practices also impact the carbon footprint of a given crop or farming operation. In fact, changes to how farmers farm could reach up to 20% of the required GHG reduction for agriculture by 2050. Some of the most impactful improvements come from production practices like variable rate fertilization, low or no-tillage, and controlled-release fertilizers.  

One specific, significant source of greenhouse gas emissions is the manufacturing of synthetic nitrogen fertilizers used to increase crop productivity. Nitrogen is needed for plants to grow, but it can’t be obtained through the air like oxygen or carbon dioxide. Ammonia is a mass-produced compound that contains nitrogen in a form that plants can uptake through the soil. Today, ammonia is commonly used in the form of urea, diammonium phosphate (DAP), compound fertilizers, and ammonium bicarbonate. 

Synthetic nitrogen is noted as the single most important element impacting nitrous oxide emissions from farmland and agricultural soils. It’s also the second-most commonly produced chemical in the world, and its manufacturing contributes 1-2% of worldwide carbon dioxide emissions. 

The carbon footprint of nitrogen fertilizer includes ammonia synthesis and conversion of ammonia to N fertilizer products as well as transportation and fossil fuel mining. 

While the invention of ammonia as a source of synthetic nitrogen fertilizer dramatically increased the number of people that a single acre of land could feed, it also had some downsides. On average, crops only absorb roughly half the nitrogen in applied fertilizers. The remaining applied fertilizer leeches off of fields into waterways or is broken down in the soil, releasing nitrous oxide into the atmosphere. 

Synthetic N has been a strong contributor to food safety as well as grain production. Farmers may be applying excessive synthetic nitrogen to croplands due to a lack of scientific guidance and the influence of traditional ideas. Proper timing, placement, and rates of synthetic nitrogen are critical to minimize nitrogen leaching and reduce the carbon footprint of nitrogen fertilizer. 

Increasing carbon footprints and a warming planet will have a negative impact on agriculture. Climate stress on crops, such as increased salinity, more extreme drought, and weed-favorable environments are expected. 

Shifting precipitation patterns will impact crop yield, by as much as 50% for wheat crops in South Asia. The combination of more challenging environments for agriculture and the increasing world population gives rise to concerns about global hunger.  

How Agmatix Can Help Reduce Your Fertilizer Carbon Footprint

Agmatix is a global agro informatics company that aims to solve data standardization challenges to increase crop yield and quality while promoting sustainable agriculture. Agmatix’s crop management software platform combines agronomy data and advanced AI into one revolutionary platform that converts data into actionable insights. 

Agmatix’s Digital Crop Advisor solution allows growers and their agronomic advisors to keep an eye on sustainability key performance indexes (KPIs). Digital Crop Advisor provides a calculation of the carbon footprint and allows users to customize fertilizer, crop protection, and nutrient plans, including controlled release fertilizers, with a planning tool. 

It’s difficult to manage what’s unseen or unmeasured.  While Agmatix can’t calculate the carbon emission of fertilizer production, we can calculate it when the fertilizer is used – providing visibility to previously difficult-to-measure information. Farmers and agronomists can easily factor fertilizer, nutrient, and pesticide carbon footprint into their management decisions, and actively work to reduce fertilizer carbon footprint while improving yields. 

Agmatix’s crop nutrition optimization solution develops unique nutrient recommendations with sustainability in mind. With these recommendations in hand, it’s possible to quantify and compare sustainability KPIs like carbon footprint and nitrogen leaching for customers. This technology makes it possible to refine previous plans or build sustainable practices in new fields.  

And because the carbon footprint information is available prior to work being done in the field, it’s never too late to make adjustments with environmental sustainability in mind. 

Our Digital Crop Advisor helps farmers reduce the fertilizer and crop protection carbon footprint of their crop production by optimizing crop nutrition management. This ensures just the right amount of fertilizer is added to the field. 

Producers won’t unknowingly apply excess amounts of fertilizer and can ensure the product is applied at the right rate, at the right time, and in the exact right place. The Digital Crop Advisor makes it simple and streamlined to optimize carbon footprint

Using Digital Crop Advisor can also help sync up application times to reduce passes through the field. With fewer fertilizer applications delivering an optimized rate, fuel use is reduced – a benefit for the farmer’s wallet that reduces the fertilizer carbon footprint. 

For the future 

The United Nations (UN) has set global goals for net-zero greenhouse gasses. This means reducing greenhouse gasses to nearly zero and planning for remaining emissions to be reabsorbed from the atmosphere. Oceans, forests, and even pastureland can be part of the reabsorption of greenhouse gasses. 

UN’s Net Zero Commitments

The UN has identified a global need to reduce emissions by 45% by 2030 and reach net zero by 2050 in order to keep global warming below the 1.5 degree Celsius warming limit set by the Paris Agreement. Staying below that warming threshold will keep the planet liveable and avoid the greatest risks of climate change. Despite global efforts from a coalition of institutions to reach net zero, current greenhouse gas emissions are not on track to reach the UN’s goals. 

Reducing both individual and agricultural carbon footprints directly ties to the UN’s net zero goals. Efforts to reduce fertilizer carbon footprint, among other efforts in agriculture, can have a broad impact on the overall carbon footprint and greenhouse gas emissions. 

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Our Commitment

Agmatix is committed to improving sustainable food production and quality. With tools like the Digital Crop Advisor calculation of carbon footprint, farmers gain an understanding of the environmental impacts of fertilizer production and application. 

Farmers can take action to reduce fertilizer carbon footprint by customizing fertilizer plans to optimize both crop nutrition and environmental sustainability. Agmatix makes it easy to connect everyday actions with environmental sustainability and carbon footprint reduction. 

Digital Crop Advisor, Your Automated Nutrient Optimization Planning Tool

Crop fertilizer supplements the needed nutrients that plants aren’t already getting from the soil they’re grown in. In order to grow and develop properly, and in turn, have a high yield, different plants require different ratios of nutrients. Different crop areas have inherently different soil nutrient levels – even within the same field. 

With the aid of precision fertilization tools, precise nutrient management customizes fertilizer inputs to what a specific crop in a specific area needs. This approach is tailored to meet crop needs as efficiently as possible while improving yield. By utilizing a precision fertilization tool, like the Digital Crop Advisor, you get decision support that ensures the right nutrient inputs are used at the correct rate and time.

Nutrient management is a hot topic for many in the agriculture industry. Recently, the United States Department of Agriculture announced additional funding for sustainable agriculture and nutrient management. With the passage of the Inflation Reduction Act on August 15, 2022, $19.5 million will go to conservation funding to support sustainable agriculture. Crop nutrition management will be incentivized through conversation programs. 

Part of that funding will go to a new outreach effort highlighting nutrient management’s economic benefits. The campaign will highlight the potential net savings to farmers who adopt a nutrient management plan – estimated at an average of $30 per acre for cropland.

If all of the 89 million acres of cropland that exceed the nitrogen loss threshold implemented a nutrient management plan, the average net savings would reach $2.6 billion. 

Beyond the financial impacts, minimizing nutrient runoff through crop nutrition optimization is key to reducing global emissions from agriculture. The Food and Agriculture Organization of the United Nations estimated that in 2019, synthetic nitrogen alone made up over eight percent of farm emissions. Integrated nutrient management is a critical aspect of sustainable agriculture.

Site-specific management of crop-essential nutrients provides field-specific optimization. In a meta-analysis of site-specific nutrient management, grain yield across all crops increased by 12%, and profitability increased by 15% while 10% less nitrogen was applied. 

Optimization of crop-essential nutrients doesn’t just provide yield and profit benefits; more precise applications and fewer fertilizer inputs can reduce leaching. Leaching results in excess soluble fertilizer escaping the crop that needs it and harming the surrounding environment. 

Precise application of fertilizer through precision agriculture and fertilization planning is a win-win for farmers, the environment, and the global population. However, implementation requires having the right data and expertise. Crop nutrition optimization planning tools can streamline the data collection and planning process, all while making it simple to connect with experts and advisors. 

Data-driven support with Digital Crop Advisor

Agmatix’s Digital Crop Advisor solution is a data-driven, AI-fueled crop nutrition decision support system (DSS) tool for automatically creating and optimizing site-specific, customized nutrition plans. Digital Crop Advisor helps you maximize yields sustainably from every crop and acre with cutting-edge technology that translates agronomic data into actionable insights. 

Our Digital Crop Advisor customized fertilization planning tool creates crop nutrition plans at the field level for applications of up to 12 nutrients. These plans are bespoke based on needs such as crops, geography, seasonality, and production goals. Both pre-season and in-season crop nutrition plans are possible. With the capability to plan for over 150 crops, even the most unique crop rotation can be managed with the crop nutrition optimization planning tool. 

The Digital Crop Advisor includes an executive dashboard that provides user-friendly access and control of the organization’s activity. With a view of the entire organization’s crop nutrition assets in a single location, users can identify issues proactively, manage crop protocols, and analyze data to extract actionable insights. 

Integrated nutrient management in sustainable agriculture is also supported by the crop nutrition decision support system by quantifying the carbon footprint of nutritional plan recommendations. Sustainability is at the forefront of the work Agmatix is doing with Digital Crop Advisor. 

Dive into the Digital Crop Advisor Features 

Global Grower Management

For farmers’ trusted advisors such as agronomists, global grower management is made easy with a main screen map-based view that shows activity for multiple growers at one time. This view serves as an agronomic data hub, making it easy to manage the availability, integrity, and security of data. 

View key grower information such as name and contact information while also seeing map-based field locations. Legacy and current agronomic data at the field level are viewable for benchmarking purposes. Global customer management streamlines the process of growing customers and growing customer success season after season. 

Precision Agriculture Capabilities

Our mapping does even more than geolocate fields! Satellite imagery with a 5-day revisit time cycle allows users to view both soil-adjusted biomass and vegetation biomass indexes. This biomass imagery allows for zone creation and precise scouting. Soil characteristic data is available, as well as crop moisture. Users get a unique bird’s-eye view of crop progress throughout the growing season, making it easy to determine field performance and assess nutritional needs. 

Nutritional Requirements

Once current field and crop conditions are well understood, crop nutrition management and optimization are simple. Users can build recommendations for up to 12 crop-essential nutrients and ensure those recommendations are specific to the crop type, variety, and expected yield. 

Our software is an integrated solution that helps field agronomists create tailored, customized crop nutrition plans which may include controlled-release fertilizers. Site-specific recommendations are generated using inputs such as yield uptake, historical crop performance, removal rate, soil characteristics, environmental impact, and more. Users can even segment nutritional needs based on phenological stages to ensure fertilizers are as efficient as possible.  

Laboratory Analysis

Soil, water, and tissue analyses are inputs to fertilization adjustments based on the crop’s specific needs. Information from these scientific sources further specifies the specific nutritional needs for crops before they’re planted and as they grow. This dataset adds increasing precision to the recommendations for nutrition management.

Nutritional Fulfillment

Agronomic data from several sources is used to create the automated fertilization plan – an actionable recommendation with measurable benefits to crop productivity and sustainability. Users can create an automated fertilization plan to meet crop nutritional requirements. The approach can be customized and adjusted based on a grower’s wants, needs, and local availability. Recommendations are compared to the specific crop’s nutrient surplus or deficiency at each phenological stage within the growing season.  

Nutritional Plan Overview

The automated fertilization plan has instant reporting functionality that can be shared with the click of a button through email, pdf, text, or WhatsApp. The plan overview includes all agronomic information, including the crop type, seasonal graphs, crop requirement tables, recommended products and application rates, and the sustainability rating of that specific crop nutrient recommendation plan. 

The report gives a comprehensive view of the most critical crop protocol management information for growers to put into action. The Nutritional Plan Overview is a great reporting feature for advisors, farmers, and applicators depending on the depth of information included. 


The nutritional plan overview includes a sustainability section that shares a detailed carbon footprint assessment of the nutrition recommendations for that crop. This feature allows benchmarking for future recommendations to continue refining the nutrition approach for crop productivity and environmental sustainability. 

Use it now!

How can the Digital Crop Advisor crop nutrition decision support system fit in an agronomic practice or on a farm? Easy-to-use functionality is available now, including pre-season management adjustments to customize nutritional recommendations based on a variety of crop protocols.  

Use pre-season and mid-season lab analysis integration (soil, water, and tissue) to make crop nutrition optimization dynamic. Global customer management, nutritional requirements and fulfillment, lab analysis, and sustainability information can all easily be at the fingertips of agronomists and growers. 

Integrated Nutrient Management In Sustainable Agriculture

More targeted crop nutrition management means more effective use of fertilizers and fewer resources wasted through leaching or ineffective application. The Sustainability Section takes the guesswork out of determining the environmental impact of crop-essential nutrients through big data. 

Benchmarking for future recommendations ensures sustainability continues to improve with additional seasons and additional data. Meeting crop nutrient needs to maximize yields while reducing environmental impact becomes easier and more precise over time. 

Environmental sustainability is an opportunity for all agriculturalists. The United Nations 2030 Agenda for Sustainable Development is aligned with five aspects of the Zero Hunger Challenge; the first pillar is Sustainable Food Systems. Supporting soil health means naturally sequestering carbon and building climate resilience. 

Among other things, principles for sustainable soil management include protecting the soil from chemical degradation, restoring degraded lands, maintaining water quality, and enhancing soil productivity based on its natural capacity. Integrated nutrient management in sustainable agriculture addresses these pillars. 

Precision agriculture tools are a data-driven way to implement crop protocol and integrated nutrition management. Agmatix’s Digital Crop Advisor customized fertilization planning tool enables farmers and their advisors to easily take action towards improving or protecting soil health while maximizing productivity and yields.

Benefits of Sharing Agronomic Data and Using Data Standardization

Agronomic data can be a powerful tool for agriculturalists. More and more, data is being generated on the farm and used across the agriculture research industry. Data can be useful in many different ways, just like a utility tool on a farm. But without standardization, data is siloed and difficult to share or use.

Standardization is Vital For Data Utility

Standardization of data, or converting it into a common format for processing, analyzing, and sharing, allows teams to collaborate efficiently. Agronomic data sharing widens the team’s effort to address agronomic knowledge gaps because everyone has access to the critical data. 

Agronomic data collaboration also helps validate agronomic practices to promote more efficient production. With supporting data, sharing the value and potential yield impact of a production practice is possible – and increases the likelihood of adoption of that practice on-farm. Ultimately, this leads to more efficient and sustainable crop production. 

Challenges Resulting from Data Separation

When data is collected asynchronously or comes from varied sources, it easily becomes fragmented and siloed. By nature, these silos prevent collaboration that enhances the value of the data. When two experts have collected data using different protocols and disagree on methodology, comparing datasets is difficult and the data inherently becomes less valuable. 

When data is fragmented, users spend valuable time trying to unite datasets from different sources into a singular structure. In a time and cost-sensitive industry, this process can waste valuable time and resources, diluting the potential for the data to make an impact. 

It’s easy for data to wind up in a separate state. Without agronomic data standardization, each researcher may use a different naming system, set of protocols, or data collection method. When it comes to validating the agronomic data, fellow researchers and peer reviewers may struggle to validate the data because of the lack of standardization. 

Benefits of Sharing Agronomic Data 

An agronomic database can assist in the sharing of agronomic data. Overarchingly, agronomic data standardization drives innovation, visibility, and market penetration for agronomic data companies. 


An agronomic database can be used to foster innovation across the industry – from farmers to researchers to agronomists. Combining the unique perspectives of professionals in the industry with the data provides the critical context and expertise to use data for insights. 

Digital precision ag technologies are one example of innovation spurred by data. Digital technologies can improve production quantity and quality while reducing labor requirements and environmental impact. 

These technologies can only succeed if agronomic data companies have access to the foundational data required to expose trends, correlation, and causation. But just having access isn’t enough – these agronomic data companies must be able to ingest and use the data, which requires it to be in a singular, standard format. 

Data can also be used to train and calibrate models. Agronomic modeling is a useful tool for understanding the complexities of crops, environments, changing climates, and interactions with production practices. Through modeling, tools can be developed to make recommendations for farmers to improve pest and disease control, protect yield from the planting date, and even recommend the best variety for a specific site. 


A perspective change is often what’s needed to draw conclusions and make decisions. In agriculture, data can provide this different perspective. Agronomic data sharing can be a tool for teaching and learning about agronomy and crop production. It can also be used to advocate leadership entities to support decision-making at high levels. 

As topics like food security, soil health, and carbon become increasingly important to global leaders, data can help experts and farmers alike determine how to produce crops sustainably, even when conditions are changing. 

Agronomic data standardization can also make data visible and useful to farmers that may not otherwise have access. Smallholder farmers may be able to adapt production practices such as fertilizer application as an example of uses of an agronomic database. 

One example of an agronomic database that increases the visibility of agronomic data is the Crop Nutrient database. Formed by the Consortium for Precision Crop Nutrition, the database provides access to global field trial data. Agriculture professionals, armed with this data, can develop crop nutrition advisory solutions to address yield, profit, and human, soil, and environmental health. 

Market penetration

Farmers may feel that the data collected on their farms adds value – but not for them. Agronomic data collaboration with companies that ensure farmers understand their rights and have access to relevant data is step one in ensuring insights from agronomic data have good market penetration. 

Consultants may also partner with farmers for agronomic data collaboration, supporting clients that are developing new products like fertilizers and bio-stimulants. 

Simplify Your Agronomic Data Standardization with Agmatix

Agmatix’s Axiom technology can be used by in-house ontologies with multiple sources to standardize data. This agronomic data harmonization platform ingests and integrates data for predictive modeling, research, and field trials. 

The GUARDS (Growing Universal Agronomic Data Standard) protocol enables agronomic data standardization in the Axiom platform by saving data into a language that’s usable by any researcher. The GUARDS protocol informs three different engines: 

  1. The Ontology engine was developed by experts to create standard definitions. This engine facilitates the definition of relations between data points and was developed with cues from the data itself. 
  2. The anomaly detection & integrity engine is powered by a technology that proactively monitors data integrity and quality using ML capabilities. The system understands and alerts for abnormal items in the data, as compared to other, similar data sets.
  3. The unit converter engine translates different measurements into a standardized unit. This helps connect and customize databases and values. 

The Axiom platform enables agronomic data insights and models through standardization. One example of a strong use for this agronomic database is comparing on-farm trial data with worldwide research data. Whether comparing dry weight vs. leaf weight, yield vs. fertilizer applied, or understanding sustainability KPIs, the Axiom platform makes it easy for farmers and researchers to collaborate and support on-farm decision-making. 

Our Axiom platform is also a helpful tool for small and large teams or teams that work with external collaborators to share and interpret data together. When the data in the agronomic database is all in the same language, researchers are able to compare apples to apples. 

This speeds up the research process while also increasing the reliability and trust in the research. This also creates alignment and increases perceived validity within the research community, rather than allowing study results to work against each other due to differing methodology viewpoints. 

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Developed and trusted by professionals

Who better to create tools to support research than the researchers themselves? Through understanding the intricacies and challenges related to agronomic data standardization, professionals were uniquely positioned to develop a platform that would address common challenges and unlock additional value. 

Across the agriculture industry, opportunities abound to use data as part of problem-solving. There are big challenges ahead, with a changing climate, increasing population, and the need for high-quality food to prevent food scarcity. Unlocking data across agronomic data companies, researchers, and farmers allows the data to inform decisions and answer important agricultural questions. 

From yield and quality to production practices to breeding and bio-stimulants, agronomic data standardization is the key to many doors which open to a better world. 

How On-Farm Experiments Can Improve Your Bottom Line

Since 1985, Illinois farmer Marion Calmer has been doing his own on-farm experimentation. And as a result of those decades of research, he’s made every corn and soybean acre $100-$150 more profitable.

He’s not the only farmer who can thank on-farm studies for improving his bottom line. Mississippi farmer Thomas Hairston shared with Farm Journal that his on-farm research proved lower cotton populations were the most profitable.

Participating in a multi-year study with the Practical Farmers of Iowa revealed to Jack Boyer he can reduce his nitrogen rate in corn. And Farm Progress reports that farmers participating in the Nebraska On-Farm Research Network gained an average $31.25 per acre.

But even if an on-farm experiment doesn’t result in a change that benefits the bottom line, it’s still valuable information.

“The purpose of doing on-farm research is not only showing me the profit potential, but it’s where I gained the confidence to make a change in my operation,” Calmer says in his YouTube video. “You can’t go out overnight and say, ‘I’m going to do something new.’ You’ve got to gain the confidence from some place, that’s what the on-farm research has done for me.”

It’s clear that putting in the effort to do your own on-farm experimentation can pay off. And with the help of technology, it’s easier than ever to set up and run your own trials.

Defining On-Farm Experimentation

As defined in a Nature Food article, on-farm experimentation is “an innovation process that brings agricultural stakeholders together around mutually beneficial experimentation to support farmers’ own management decisions.” The research occurs in farmers’ fields, at scales meaningful to them. 

There are six principles of on-farm experimentation

1. Farmer centric: Farmers fuel the research process

2. Real systems: Uses farmers’ own management and scales

3. Evidence-driven: Insights are anchored in data

4. Expert-enabled: Specialists add value

5. Co-learning: Emphasis on engaging by sharing

6. Scalable: socializing mechanisms

While there are benefits to collaborating with ag extension personnel, scientists and other farmers in research, growers are not limited to doing meaningful research with others. As long as they understand the basic principles of designing and executing a trial, growers can succeed with their own independent studies. Especially if they can tap into the power of precision ag technologies and digital tools.

Technology Key to On-Farm Experiments

Precision ag has made it easier than ever for farmers to conduct their own experiments and farmers are seizing the opportunity. John Fulton, an ag engineer at The Ohio State University, told CropLife that results from a recent survey found that nearly 85% of growers using precision ag technology are doing on-farm experiments.

GPS guidance can pinpoint trial boundaries, input application technologies can make sure a product is applied at the right rate in the right place, and yield monitors make for easier data collection. 

Growers can also use precision ag to identify potential research areas. Yield maps can identify yield inconsistencies throughout a field, while aerial imagery can detect potential pest problems, wet spots, or other issues worth exploring.

But just because these technologies make it easier to execute on-farm experiments, they don’t guarantee that a farmer is setting up their trials properly or interpreting the data correctly. 

To make sound decisions based on the results of a research study, the trial must be set up for replication and randomization. It’s not uncommon for a grower to do a simple side-by-side trial, with half the field under treatment and the other half the control plot. But as NC-ANR Academy explains, replicating and randomizing treatments is what allows the data to be statistically verified, so farmers can be confident the results of the trial are due to the treatment and not by chance or other factors. Without the assistance of digital tools to design these trials, growers are at risk of investing time and resources into a study that may not produce usable information.

Kansas State University Research and Extension precision ag economist Terry Griffin, who is a member of the Frontiers in On-Farm Experimentation, also points out that farmers are still missing a standardized way to collect data and easily use it to benefit their operations. He calls for the need of “automated, rigorous computer algorithms,” to prevent human bias, saying that “even the best scientists sometimes have a bias to them.”

Agmatix App Simplifies Trial Setup, Data Collection and Interpretation

Agmatix recognizes the need to better design on-farm experiments, collect data easily and have confidence in the results. Which is why we’ve launched the free Agmatix app for on-farm experimentation for growers. 

Whether a grower is online or offline, the app will help them conduct an experiment without any assistance. In a matter of seconds, they can set up basic trial information, set the treatments so they’re both replicated and randomized, set the desired measurements, and have a standardized way to collect research data that is preserved and secure. The app can also statistically analyze the data so they can have confidence in the decisions they make based on the results.

The app we’re launching will also help connect interested farmers with ongoing trials near them, as well as past trial data on relevant crops and products they may be interested in. 

The Agmatix app is free and supported on both Apple and Android devices.

The app is available in the and , so you can start planning your on-farm experiments for next season. 

And if you need help taking your on-farm experiments to the next level, our Agronomic Trial Management software can help you plan out a statistically verified trial, guide you with end-to-end trial management, standardize collected data, and provide valuable insights based on the results.

Ensuring Productive Food Systems with Agmatix

October 16th is World Food Day. It commemorates the founding of the United Nations Food and Agriculture Organization (FAO) in 1945. It reminds us to reflect on food production, world hunger, and sustainability. 

It’s a critical time to be considering these factors. The COVID-19 pandemic, climate warming, inflation, and international tensions in recent years have all impacted the global struggle for food security. Nearly 10 percent of the global population suffered from hunger in 2020, a sharp rise compared to 8.4% in 2019. 

A dramatic increase in prices for critical foods like wheat, barley, rice, rapeseed, and sunflower oils is moving vulnerable countries into a food crisis. Increasing costs for critical inputs are partly to blame. And the changing climate is increasing pests and diseases, all while changing the nutrient makeup of staple crops. 

By the numbers, ⅔ of those experiencing acute food insecurity are rural food producers. 3.1 billion people – representing nearly 40% of the world’s population – cannot afford a healthy diet. Women are 15% more likely than men to be moderately or severely food insecure. 

In 2021, 193 million people experienced high acute food insecurity. High acute food insecurity necessitates humanitarian assistance to survive. Over half a million endured catastrophic conditions, resulting in starvation and death. 

This environment is not so different from the one in which the FAO was founded. In the later years of the Second World War, global leaders recognized the importance of nutrition and the criticality of addressing agricultural challenges using science and technology. 

The FAO was established with the goals of raising nutrition and living standards globally, improving food production and distribution efficiency, and improving the condition of rural populations. As the FAO has evolved, it has benefitted the expanding world economy and increased global freedom from hunger.

Production By the Numbers

Agriculture is a growing contributor to the world economy. Between 2000 and 2019, global value added from agriculture, forestry, and fishing grew by 73%. Agriculture was also an employer of 27% of the global workforce. 

In the same time period, the production of primary crops hit a record high and grew 53%. Sugar cane, maize, wheat, and rice make up half of the global primary crop production. 

Both vegetable oil and meat production increased between 2000 and 2019. Vegetable oil production, driven by demand for palm oil, has more than doubled. Meat production has grown by 44%. 

China, India, the United States, and Brazil are the world’s biggest food-producing countries. They have a sizable land mass, proper climate zones, and a large population supporting their agricultural production. 

China is the world’s largest agricultural producer, pumping out $1.5 trillion in annual output. China is also the world’s most populous country, but only has 10% of the world’s arable land. China’s eastern and southern regions are highly productive, leading the country to produce one-fourth of global grains. China also leads the world in cereal grain, cotton, fruit, vegetable, meat, poultry, egg, and fishery production. 

Despite the high production, China has moved away from full self-sufficiency in 2000. In 2020, the country imported nearly 23% of its food needs due to declining soybean output and loss of farmland. In 2019, China became the world’s leading importer of agricultural products. 

India has both the second-largest population and second-highest agricultural output in 2020. India leads the world in the production of milk, jute, and pulses. It’s second in the world in the production of rice, wheat, sugarcane, fruit, vegetables, cotton, and groundnuts. 

India is the world’s largest exporter of refined sugar and milled rice. India was the 9th biggest exporter of agricultural products in 2019. 

The United States follows China and India in agricultural production. However, the U.S. has a fraction of the agricultural workforce of China or India. Top commodities for the country include corn, soybeans, dairy, wheat, and sugar cane. 

The U.S. led the world in agriculture exports in 2020. China, Canada, Mexico, and Japan are leading importers of U.S. agriculture products. California made up 13.5% of the U.S.’s ag production in 2020. 

Fourth-ranked for agricultural production is Brazil. The Brazilian economy has long focused on agriculture. Brazil’s exports ranked third, behind the U.S. and the Netherlands. The country is the top exporter of soybeans, raw sugar, and poultry. China imported nearly $30 billion of Brazil’s agricultural exports in 2020.  

Between 2009 and 2050, the global population is expected to increase by a third. Feeding close to 10 billion people in 2050 will require a 70% increase in food production. In developing countries, agricultural production will need to almost double. Annual cereal production will have to grow by almost one billion tonnes and meat production by over 200 million tonnes. High-quality and high-volume agricultural products will be required to prevent increasing food insecurity.    

How Can We Continue to Produce Better Food? Agmatix Can Help

Agmatix is dedicated to equipping farmers and their advisors with tools for using high-quality, standardized data to improve food production with a lower environmental impact. As food production volume and quality become more critical with population growth and changes in climate, increased precision agriculture and data-based decision-making will be required to help advance food security. 

Agmatix’s agro informatics tools support global agriculture production. From corn to coffee, over 150 different crops and crop-essential nutrients are represented in our data. Agronomic Trial Management, the Open Data Crop Nutrient Platform, and the Digital Crop Advisor empower field-level decisions with high-level data and powerful insights. 

Agronomic Trial Management

On-farm experiments help to understand the localized response to a specific production approach. Using the outcomes of an on-farm field experiment to inform decision-making can be a powerful tool to improve productivity, but the process of executing the trial and analyzing the outcome can be burdensome. Agronomic field trial management can be a challenge for farmers. 

Agmatix makes it easy to plan, monitor, collect data, and analyze field trial outcomes.  Advances in agricultural tools and technology, such as our Agronomic Trial Management tool, can help improve crop health, yield, and quality. Ultimately, harnessing agronomic trial data can lead to helping advance food security. 

Planning the field trial is straightforward with Agmatix’s holistic, on-map planning process. A layout planner allows users to select the design methodology that works best for their on-farm research. Hundreds of treatment combinations are available. 

Once the agronomic trial is ongoing, an end-to-end project management module simplifies visibility and control. Researchers and field trial operators can communicate directly. Users can assign tasks and monitor task status. 

With Agmatix, standardizing collected data is easy, allowing users to efficiently evaluate trials. A user-friendly data collection tool unlocks data for comparison and prevents data loss. And instant reports and analysis allow for quicker decision-making. 

With Agmatix, farmers can harness the power of using agricultural technology to streamline field trials and do their part to advance food security. 

Global Crop Nutrient Removal Database

Understanding the sustainability of crop nutrient programs goes hand-in-hand with long-term food security. Agmatix has partnered with the Consortium for Precision Crop Nutrition, whose Global Crop Nutrient Removal Database is a resource to scientifically estimate nutrient removal and efficiency in the agriculture production environment. This database helps create site-specific recommendations for the most sustainable nutrient management. 

Crop yield and residue and their respective nutrient concentrations are the factors that influence crop nutrient removal. Farmers can improve crop management by understanding crop nutrient removal rates and long-term trends of nutrient removal rates. This data will help make agriculture more sustainable and help fight for food security worldwide.  

Digital Crop Advisor

Digital Crop Advisor is a precision agriculture tool that uses technology, data, and a decision support system to optimize crop nutrition. Crop-specific data supports sustainable nutrition management to create high-yielding, high-quality crops that help feed the world and help advance food security. 

Digital Crop Advisor allows farmers to get specific with sustainability. They can monitor sustainability key performance indicators – like carbon footprint and nitrogen leaching – to make the best decisions for their farm and the environment. 

Seamless crop nutrition optimization recommendations and organic manure calculations help farmers easily implement sustainable practices. And the Digital Crop Advisor even integrates with lab analysis data from tissue or soil samples, so farmers can use all the data they collect on the farm to fuel decision-making. 

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5 Tips for Designing a Successful On-Farm Field Trial

World Food Day and Agmatix

This World Food Day is a perfect time to consider taking your farm or business to the next level of sustainability with Agmatix. Precision agriculture technology that uses standardized data to inform decision-making at the field level will help farmers produce more high-quality food while minimizing environmental impact. And that’s what it will take in the continuous quest for food security. 

Agmatix makes using data and agricultural technology on the farm easy. With Agronomic Trial Management tools, the Global Crop Nutrient Removal Database, and Digital Crop Advisor, farmers and their advisors can make data-based decisions at the field level. On-farm experiments, crop nutrient removal data, and optimized nutrition plans all fuel sustainable agriculture practices. 

On this World Food Day, we consider those around the world that are struggling with hunger, those that work hard to produce food, and those that work every day to enhance the sustainability of world food production. There’s a great opportunity to harness the best agricultural technology to make a difference in the lives of millions by addressing food security and building a better world of tomorrow. 

Save Time, Increase Sales and Gain Farmer Trust with Digital Crop Nutrition Support

Crop nutrition management has never been a one-size-fits-all approach. Several variables factor into a farmer’s fertilizer plans. And now they’re facing unique circumstances that make developing an effective and efficient strategy even more difficult.

Field agronomists need to develop customized crop nutrient plans that navigate these challenges while still producing a high-yielding, quality crop. That means making scientifically-backed recommendations based on high-quality data. With the right crop nutrition digital support system, agronomists can be confident that their plans will deliver exactly what the farmer needs. 

Farmers’ Challenges Affect Fertilizer Plans

The importance of developing an efficient, effective fertilizer plan has never been more important than we’ve seen in the last year.

Farmers faced record high fertilizer costs in 2022, and though prices are cooling off, they’re still looking at tight margins in 2023—especially since, as farmdoc daily points out, many farmers were able to lock in fertilizer prices for the 2022 season while they were lower in 2021. That opportunity for 2023 does not exist.

As a result of these prices, and in some cases fertilizer shortages, president and CEO of The Fertilizer Institute Corey Rosenbusch told AgWeb that farmers should lean on their retailers and other agronomic advisors to help them be as efficient with their products as possible. 

Fertilizer prices aren’t the only factor driving the need for efficiency. As Reuters reports, consumers are pressuring food producers to support farms using sustainable farming practices. So companies like PepsiCo are now sourcing sustainably grown ingredients. 

Environmental concerns from nutrient runoff are also pushing farmers to adopt sustainable practices. In some places, like the Western Lake Erie Basin in Ohio, there are restrictions around fertilizer application. While other states like Iowa have voluntary regulations that growers may be trying to abide by, especially with the growing demand for enforceable restrictions.

Complexities in Meeting Crop Nutrient Needs

On top of trying to keep costs low and ensuring a fertilizer program is the most sustainable it can be, agronomists still need to create a plan that provides crop-essential nutrients needs so that growers can still have healthy, high-yielding fields.

That’s no simple task given that they need to account for:

  • Crop type and its specific macro and micronutrient needs
  • Crop rotation
  • Soil type and conditions
  • Other management factors, such as tillage practices
  • Weather conditions
  • Available input options
  • Labor, equipment and technology available

All of those factor into designing a crop nutrient plan and determining which fertilizer products to recommend. 

Data-Driven Digital Tools Remove Guesswork

Given the complexity of creating a crop nutrient plan, agronomists need data-driven digital solutions to ensure they’re accounting for all of the different variables and designing a fertilizer program that best meets their farmers’ needs.

When built on a wealth of high-quality data, a crop nutrition decision support system can take all of the specific variables, from weather to crop prices to the impact on the environment, and provide insight into what would be the best fertilizer plan based on a grower’s budget and goals.  

Ultimately, it can help build trust between agronomists and growers. Because data removes any bias an agronomist or grower may have, it helps avoid decision-making that’s based on emotions or gut feelings. Growers can trust that their agronomists aren’t just trying to sell them a product. All parties can feel confident that what’s being recommended is the best plan because the science and facts back it up.

Optimize Crop Nutrient Plans for 150+ Crops

Agmatix’s Digital Crop Advisor delivers exactly what agronomists need—a scientific-based crop nutrition decision support system that provides customized guidance for their farmer customers.

Digital Crop Advisor is built on 12 scientifically proven crop nutrient data profiles, which allows agronomists to create unique nutrient plans for over 150 different crops, using data integration of crop-essential nutrients.

It’s also the first crop nutrition optimization planning tool that can account for controlled release fertilizers. Field agronomists can include these fertilizers in their crop nutrition management plans and see the nutritional distribution along the different phenological stages of the crop. This includes the expected depletion date of the controlled release fertilizer, so they can schedule the next fertilizer application at the optimum time.

Not only does Digital Crop Advisor tailor nutrient plans to the specific crop, it also taps into data from previous customers’ plans or other fields using our technology to provide sustainable nutrient recommendations. Agronomists can quantify and compare sustainability KPIs, such as the program’s carbon footprint or if there’s susceptibility for nitrogen leaching. Each plan will show the total carbon emissions and a percentage of how each nutrient contributes to that total.

Digital Crop Advisor is also adaptable. Suspect crop prices will take a dip or wonder how the plan would change if you got above average precipitation? Run different simulations and the customized fertilization planning tool will correctly adjust crop nutrient needs so you can compare recommendations.

And agronomists can create a customized nutrient plan instantly. Our software tool rapidly integrates field boundaries, creating an automated fertilization plan quickly, accurately, and efficiently.

Farmers are under a lot of pressure to grow crops that will still benefit their bottom line, meet their buyers’ yield and quality expectations, and do so in a way that doesn’t harm the environment. The right nutrient plan is crucial in this, and with the right crop nutrition decision support system, agronomists can become their trusted partners in making that a reality. See how Agmatix’s Digital Crop Advisor can help your agronomists become that trusted partner and optimize their crop nutrition management plans. Contact us today to schedule a demo.

Coffee: Balancing the Complexity of Production and Providing Caffeine

A cup of coffee is a revered part of many people’s morning rituals. Whether it’s a cup with friends or work day savior, over 2 billion cups of coffee are consumed daily and the global coffee market was valued at a staggering USD 465.9 billion in the year 2020! 

Since October 1 marks International Coffee Day, we wanted to share some background on the process of coffee production, where coffee is produced in the world and the unexpected but important role of agronomics in coffee quality and production. 

Understanding the Coffee Production Process

While a delicious cup of joe might magically appear out of a coffee pot each morning, there’s an interesting backstory on the beans and how they make it into our cups. There’s a ten-step process from plant to bean to brew. 

  1. Planting: Coffea trees are shrub-like plants that were domesticated in Ethiopia. They grow from a coffee bean – an unroasted one, of course! Coffee plant cultivation involves planting in beds, protecting seedlings from direct sunlight, and watering frequently. 
  1. Harvesting: Coffee trees can take three to four years to bear fruit. Called coffee cherries, the fruit of coffee trees are bright red when ripe and often require hand-picking due to ripening time variability. In some places, particularly where the plantations are flat and large, harvesting has been mechanized. Cherries can either be picked by stripping all the fruit off an entire branch at once, or individually based on their ripeness. Typically, there is one main harvest of coffee cherries per year. 
  1. Processing: Cherries are processed quickly after harvesting to avoid spoilage. Processing can be done using a dry method or a wet method, depending on local resources. The dry method involves spreading freshly picked cherries on large surfaces to dry in the sun and raking them throughout the day. 

The wet method removes the coffee cherry pulp to dry the cherries with only the parchment skin. The cherries travel through a pulping machine to separate the skin from the pulp, and then the beans are separated by weight as they sink or float in water channels. Heavy, flavorful fruits will sink. After being separated by rotating drums, the beans are fermented in water. 

  1. Drying: After 12 to 48 hours, wet method processed beans must be rinsed and dried. Beans are sun-dried or machine-dried in large tumblers until they reach 11% moisture. 
  1. Milling: The milling of coffee cherries is a multi-step, pre-export process. Wet or dry processed coffee is hulled to remove the parchment layer or the entire dried husk from the cherries. Polishing may be done to remove any remaining silver skin. Then, beans are sorted and graded by size, weight, color flaws, and imperfections. Beans can be sorted using air jets to separate beans by weight. Defective beans are removed. 
  1. Exporting: The beans are ready for international travel. They’re loaded onto ships in shipping or plastic-lined containers. 
  1. Tasting: Coffee tasting, or “cupping”, is done by professionals looking for bean visual quality, aroma, and taste. Beans are roasted in a small roaster, then ground and infused for the copper to smell and taste. Coffees are evaluated for the purpose of blending different beans or building the right roast. 
  1. Roasting: Beans are roasted to convert them from green coffee into aromatic beans that are ground and used to make that cup of joe. Beans are roasted at about 550 degrees Fahrenheit. Once the beans reach 400 degrees, the oil inside the beans begins to emerge and creates the well-known coffee flavor and aroma. Beans are cooled by air or water. Once roasted, beans are on the clock for reaching the consumer. Once roasted, beans are on the clock for reaching the consumer. 
  1. Grinding: Beans are then ground to the appropriate coarseness for the intended brewing method. The finer the grind, the more quickly coffee should be prepared. 
  1. Brewing: The last step in the coffee process is extracting the coffee through brewing. Coffee can be brewed in many different ways, depending on the grind and drinker’s preference. For example, espresso machines use fine coffee and high pressure to extract coffee and make the perfect latte or macchiato! 

Coffee Around the World

Coffee has as diverse growing locations as it does drinking locations. Over 50 countries around the world produce coffee, though the ideal location for coffee cultivation is along the Equatorial zone, between latitudes 25 degrees North and 30 degrees South. This area is referred to as “The Bean Belt”. Different varieties of coffee thrive at different altitudes, in different soils, and at different temperatures. 

Guatemala, Costa Rica, Columbia, Brazil, Ethiopia, Kenya, the Ivory Coast, Yemen, Indonesia, Hawaii, Mexico, Puerto Rice, and Vietnam all have notable coffee production. Coffee from different areas produces different flavors and aromas. 

Hawaiian coffee takes advantage of good rains, black volcanic soils, and tropical clouds to provide a rich, aromatic, medium-bodied coffee. In Puerto Rico, two major growing regions produce coffee with a balanced body and acidity and a fruity aroma. Indonesia is known for fine-aged coffees with a deeper body and less acidity. Vietnamese coffee plant cultivation happens on small plantations but the country is quickly becoming a major coffee production powerhouse. Much Vietnamese coffee is used for blending due to its mild body and light acidity. 

The quality and flavor of coffee are dependent on many variables. Plant variety and genetics, soil, climate, rainfall, sunlight or shade, altitude, and nutrient inputs all change the characteristics of coffee. For example, Guatemalan coffee grown at altitudes of 4500 feet is described as “strictly hard beans” and has a unique spicy or chocolatey complexity. Yemeni coffee cultivation happens in areas where water is sparse and the beans tend to be small and irregularly shaped, with a deep, rich, distinctive flavor. 

The Agronomics Behind the “Cup of Joe”

Coffee plant cultivation requires agronomic expertise. Soil, rainfall, shade, and wind all answer the question of what affects coffee production. 

Soil requirements for growing coffee include deep, well-drained soils. Oftentimes, volcanic-origin soils are good for growing coffee. Leached topsoil, poor drainage, or solid rock near the surface of the soil will not meet the coffee trees’ requirements for growing. 

Coffee will perform well in soils that handle high rainfall by distributing the moisture in the soil. However, fertilizer leaching is a risk in these areas, requiring intentional management for coffee plant cultivation sustainability. 

Rainfall distribution is important for coffee production. Too much moisture can increase vegetative growth and reduce fruiting, while a short dry period can help synchronize the cropping cycle. Plantations can irrigate to manage the moisture needs of the coffee plant.

Shade can be used intentionally by coffee growers to address climates that are too warm for coffee. Restricting light can also prevent trees from overbearing in areas where fertilizer supplies are limited. 

Coffee trees are susceptible to wind and require a windbreak to prevent tearing, cupping, and removal of leaves or even ripe cherries. 

What affects coffee production?

Outside of Mother Nature, coffee characteristics can be heavily influenced by cultivation practices. Coffee plantations will take fertilizer and irrigation requirements into consideration as well as pesticide application needs. 

The first five years of a coffee plant’s life are the most critical. During this time, coffee plant nutrition needs must be met to encourage vigorous root and leaf growth. Young trees have high phosphorus requirements to promote root production. 

Once trees are bearing fruit, the coffee plant nutrition needs change to sustain leaves, stems, roots, and fruit. In the plantation orchard system, pruned wood and coffee leaf litter return nutrients to the soil. But, nutrients may be lost by leaching, erosion, or volatilization. Farmers may apply fertilizer for coffee nutrient management through an irrigation system or broadcast it by hand. 

Second-year and older trees can have leaf tissue analyzed to identify any nutrient imbalances. Tissue tests can identify nutrient deficiencies before they become visible symptoms.  Fertilizers for coffee plants can be customized based on the results of the tissue analysis. 

Irrigation is an important topic in coffee cultivation. In areas with less than 60 inches of rainfall a year, irrigation is recommended, though water needs are often referred to in terms of “crop coefficient,” or the crop’s water demand in relation to the evaporation occurring in an open pan of water in the orchard. Water needs also differ for young, nonbearing trees and two-year and older trees.  

Drip or micro-emitter systems are often used on plantations. Applying water is a balance between cost efficiency and plant health. Overirrigation is a risk for coffee plant cultivation and can cause poor root development and even death. Overirrigation is more likely if there is a solid rock pan below the topsoil that catches water and allows it to stand. 

Weeds, diseases, and insects can be other challenges to growing coffee. Coffee plantations can control what major weeds they experience through manual or mechanized means. The major vines of concern are morning glory, ivy gourd, and bitter melon. Weed control can cost up to 10% of annual growing costs. Groundcovers can be used preventatively for weed control. 

Green scale is one of the most impactful pests for coffee as it sucks sap from the coffee plant and covers the leaves in black sooty mold that reduces photosynthesis. Green scale can be biologically controlled with white halo fungus. Growers can also use soil or foliar applied imidacloprid to control green scale. 

Black twig borer is another damaging insect in coffee plant cultivation. It causes wilting and death of leaves and wood, leaving bark black. The best control for these beetles is keeping trees healthy and pruning infested laterals. 

Coffee is also susceptible to nematodes and disease. Root-knot nematodes enter and feed on roots, disrupting growth. Cercospora leaf spot is a common fungus in coffee-growing areas but can be controlled by managing growing conditions and coffee plant nutrition needs. 

Other funguses to which coffee is susceptible include coffee leaf rust and coffee berry disease. Coffee leaf rust causes yellow-orange lesions on the leaves, and the fungus is spread by wind, rain, or even the clothing and coffee bags around the coffee trees. Copper fungicides and resistant varieties are the main methods of control. 

Coffee berry disease causes brown, sunken lesions on green cherries and eventually will destroy the bean. Quarantine is the best control for the fungus. The most aggressive strain of coffee berry disease is found in Africa, though other strains are seen worldwide. 

What are the challenges of growing coffee?

In recent years, coffee production has been troubled by a variety of challenges. Around the world, June 2022 production estimates have been lowered from the December 2021 projections. Too much rainfall and cloud cover has cut back Columbian crop production, while Honduras production estimates have dropped 1.4 million bags due to leaf rust slashing yields. Brazil’s drought and cold cultivation season in 2021 caused farmers to cut down coffee trees.  

With harvest 2022 in sight, Brazil’s coffee crop is projected to be at its lowest since 2014. This year’s arabica cherries have smaller than usual beans leading to disappointing yields. Smaller beans mean more are required to fill weight-based bags, and overall output is reduced. 

Sustainable Production and Improved Quality with Agmatix

Coffee crop cultivation can be a challenge! Between pests, disease, climate sensitivity, and meeting plant nutrition needs, attaining high yields and good quality cherries can feel very difficult. The good news is that crop management software can help collect data and support decision-making for the most productive, most sustainable crop possible. 

Agmatix is an agro informatics company dedicated to transforming data into insights. For coffee growers, the Digital Crop Advisor platform can help optimize crop nutrition management, customize fertilization planning, and monitor sustainability KPIs of nutrition plans and agronomic practices. 

Our Digital Crop Advisor is a decision support system with scientifically-proven data to inform specific crop protocol management. Insights are based on over 150 crops and crop-essential nutrients, and multi-device support makes it easy to optimize crop nutrition with the planning tool. 

The Digital Crop Advisor also simplifies coffee nutrient management with seamless crop nutrition optimization plans through a customized fertilization planning tool. It’s key to meet coffee plant nutrition needs, but those needs may differ based on plant age, growth stage, climate, and more. Because fertilizer for coffee plants has a risk of leaching, especially in certain soil types, precise and well-timed applications are key. Digital Crop Advisor makes balancing meeting coffee plant nutrition needs with protecting the environment easier than ever before. 

Agronomic data insights are available through the analysis of aggregated and standardized data. Both legacy and ongoing research data can be visualized and analyzed to support decision-making. Agmatix also makes it easy to harness the expertise of advisors and researchers through a collaboration wizard.  

Understanding the environmental impact of decision-making in coffee cultivation can be challenging. The Digital Crop Advisor allows users to monitor sustainability KPIs such as carbon footprint and nitrogen leaching. Integrated support of lab analysis is supported, and the customized fertilization planning tool helps producers understand the environmental impact of nutrient recommendations before they are used on the plantation. 

While “sustainability” is a buzzword in many areas of agriculture, coffee production can have a  big environmental impact, and coffee trees are particularly sensitive to changes in climate, making changes in climate of particular concern for coffee plant cultivation. Coffee quality can be negatively impacted by changing light exposure, altitude, water stress, temperature, carbon dioxide, and nutrient management. Using tools like Agmatix’s Digital Crop Advisor is a win-win for higher production, better quality, and sustainable production for the future of a good brew.  

Agmatix’s Commitment to a Zero Emissions Future

Zero Emissions Day, September 21st, is a day to pause and think about greenhouse gas emissions and the future we envision for the planet. It is a reminder that preserving the Earth in a liveable state requires the global temperature increase to be limited to 1.5 degrees Celsius. The Earth is already roughly 1 degree Celsius warmer than pre-industrial levels

Net zero is the state in which any greenhouse gas emissions are either eliminated or re-absorbed from the atmosphere. Reaching net zero will require all hands on deck, across countries and industries. It provides an opportunity for agriculture to reduce its carbon footprint, too. 

Agriculture plays a big role in global emissions. According to the U.S. Environmental Protection Agency (EPA), agriculture is responsible for roughly 18% of global greenhouse gas emissions. And that number is increasing; over the last forty years, agricultural emissions stemming from human activity have increased by 30%. Recent activity has impacted agriculture’s emissions. 

A majority of the 669.5 million metric tons of carbon dioxide equivalent emissions from agriculture came from direct nitrous oxide, and direct methane was also a big contributor. The good news is that agriculture emissions were roughly four percent lower in 2018 compared to 2000. However, nitrous oxide emissions from synthetic fertilizers and crop residue incorporation were more than 35% higher in the same period. 

Agriculture is also at risk from emissions. Climate change is expected to reduce corn, soybean, rice, cotton, and oat yields starting even as early as right now! This could increase the need for irrigation in crop production, all while regional water availability continues to be a challenge. 

Weather patterns are expected to change. Farmers are expected to have the flexibility to adjust production practices to changing weather and resources, but flexibility could be harnessed now to reduce the carbon footprint of agriculture

There’s a global effort to reach net zero. Agriculture is a key to reaching this goal. More than 70 countries have set a target to reach net-zero emissions, and over 1,200 companies have set targets as well. 

Innovative solutions are essential to meet the challenges the world is facing today in agricultural production. The more information farmers, researchers, and agronomists have, the better the chances to leverage agricultural big data to make informed decisions in the field that will result in higher yields, better crop quality, and lower environmental impact. 

Agmatix is one such company providing innovative solutions for agriculture because sustainability is a foundational part of who we are. Agmatix helps agronomists, researchers, and farmers customize crop nutrition recommendations based on a verified, scientific-based crop nutrient decision-support system that not only improves yield but also provides a sustainability scoring index for each crop’s nutrient management plan.

Agmatix’s Commitment to Sustainability

Agmatix is committed to helping reach the zero-emission goal by 2050. Our unique data science and AI agricultural platform transforms agricultural big data into actionable insights for farmers, researchers, and agronomists to make informed decisions to improve crop yields, and nutritional quality, while ultimately helping reduce greenhouse gas emissions and the agricultural carbon footprint.

Plant nutrition carbon footprint optimizer

The Digital Crop Advisor solution uses agronomic field trial data to allow farmers to optimize crop nutrition – applying just the right amount to give plants what they need, without an unnecessary runoff, waste of resources, and lower environmental footprint.

With Agmatix, farmers can calculate the carbon footprint of their fertilizer plans based on field characteristics, agronomic practices, crop and fertilizer type, and more. Farmers can even run simulations of different recommendations to compare environmental and yield tradeoffs to learn how to reduce their agriculture carbon footprint. 

Personal environmental responsibility and employee volunteering

Agmatix is also committed to a culture of sustainability. Employees are encouraged to take personal environmental responsibility and volunteer in ways that positively impact the world we live in. 

You Can Lead this Zero Emissions Day

Opportunities abound to be a part of Zero Emissions Day. At home, select energy-efficient products. Even small changes such as unplugging your phone as soon as it’s charged and turning the heat down a single degree can make a big difference! 

On the go, find opportunities to cycle or hop on the bus. Carpool when you can, or try taking the train.

When it comes to food and agriculture, don’t forget about local and seasonal products. Give alternative proteins a try. Avoid food waste by buying what you need and using it all. Compost any food waste you do have. 

On the farm, the USDA suggests that changes in production practices could both cut greenhouse gas emissions and pull carbon from the atmosphere through carbon sequestration. 

This is a great opportunity for agriculture to take the lead in carbon footprint reduction! How might this happen? Through things like cover crops that, in the right conditions, can reduce erosion and nutrient runoff. Or producing biofuels that replace fossil fuels and can impact emissions across many industries. Reducing or eliminating tillage can impact soil health and carbon content as well as energy use on the farm. 

For a Better Tomorrow 

Agriculture has the added challenge of reducing carbon footprint while feeding a growing population. Ron Baruchi, CEO of Agmatix noted that “Growers, agronomists, researchers and ag industry experts are tackling today’s biggest challenge – providing food security for the world’s growing population.” With improved crop management decision-making, better crop quality, higher yields, and lower carbon footprints are within reach. 

A swift change is needed in agriculture to reduce the carbon footprint of agriculture. With a big goal of a 45% reduction in emissions by 2030, farmers and the agriculture industry can help get sustainability trending in the right direction. 

Together, Agmatix and farmers can better understand the carbon footprint of individual farms using. Farmers can make informed decisions about nutrient programs and their impact on the farm’s carbon footprint. By growing data for impact, Agmatix and farmers are growing a better, more sustainable tomorrow.

Continued Innovation at Agmatix

We, at Agmatix, are committed to helping our customers make field-level decisions and gain actionable insights from their agronomic data. The agriculture industry is facing a number of challenges, such as the rapidly growing world population, climate change, supply chain disruption, and limited resources. This is why we continue to innovate and bring the latest solutions to address these challenges!

As an agro informatics company, our goal is to support agriculture professionals worldwide in using big data to make informed decisions. We do this through three core solutions: Insights & Models, Agronomic Trial Management, and the Digital Crop Advisor. Learn more about these solutions below.

Agronomic Trial Management

With our Agronomic Trial Management solution, it’s never been easier or more efficient to plan, run, and analyze your field trials. The solution’s interface has been redesigned for greater ease of use and improved navigation. In addition, users can drag and drop their trial layouts on a map, and create repetitive protocols and customizable data collection forms. 

The Agronomic Trial Management platform allows for flexible data collection using mobile devices, tablets, or a desktop, as well as field-level reporting. This feature allows users to create trial plans and perform analysis on the go. 

Get the visibility needed to control your field trials in real-time  

Our solution helps you streamline your workflow and better collaborate with researchers and field workers by providing automatic status updates and task assignments. With full visibility of your research trials, you have the added capabilities for governance over trial protocols and task forms to help you streamline collaboration and analysis. This tool for managing field experiments enables you to “be in the field” from wherever you are.

 Standardize collected data for comparison, evaluation, and data loss prevention

Our user-friendly agronomic collection tool automatically standardizes field data as it’s entered and preserves it using our GUARDS protocol. For data entry, a wide range of agronomic domains and parameters are possible and we support both iOS and Android devices.

Insights & Models

We can help you unlock true value from your agronomic data. Our Insights & Models solution analyzes and standardizes data from your field trials or experiments and converts it into power agronomic actionable insights & models. 

The Insights tool is equipped with additional statistical capabilities most frequently used in field trial analysis (paired t-test, independent t-test, one/two-way ANOVA, and Tukey-Kramer) to bring data science capabilities and agriculture predictive analysis to your fingertips.

Access and Analyze all of your agronomic data in one unified place

Our user-friendly interface provides you with access and viewing capabilities of all your agronomic data in one unified place. We can ingest and harmonize your legacy trial data so you can easily compare that to your ongoing field trial data (using the Agronomic Trial Management) and perform cross-trial analysis.

With our Insights solution, you can visualize and analyze your field trials in a single location and access your data at any time. Our pre-built advanced statistical analysis widgets help you easily create customized on-demand reports to analyze your trial data, enabling you to make data-driven decisions and optimize your R&D efforts.

Collaborate with researchers and extract exactly what you need

We understand that no two research data sets are the same. That’s why our tools allow you to standardize data from multiple experiments, no matter where your research collaborations take you. 

Calibrate and verify statistical and machine learning models

With our platform, you can create data-driven predictive models in a single workspace. Our insights and agronomic modeling solution combine data science with agronomic trial data to help you apply agro informatics best practices.

Start Analyzing Data with Advance ML Models

Digital Crop Advisor

Build stronger relationships with your customers and optimize growers yields sustainably. With our state-of-the-art technology and data insights as a decision-support system for crop nutrition management, you can gain complete operational overview capabilities within our management dashboard. 

Managers can get an overview of all operations, and see how specific products are performing in sales and crop yields across the globe. This dashboard also allows you to oversee the environmental footprint of the recommended nutrition plans, ensuring continuous sustainability improvements. 

Operational control and visibility of your organization’s crop yield and nutrition, product performance, and sales

From a single location you can track and monitor your organization’s nutrition recommendations across all agronomy and sales teams. Get real agronomic actionable insights into the number of fields and coverage of each operation regionally and globally!

Our digital agronomist sales support tool also includes an easy-to-use dashboard that allows you to filter by time, crop, and more to help with data-driven decisions.

Empower field-level agronomists and agriculture professionals with verified, scientific-based crop nutrient decision-support engine

With Digital Crop Advisor, you can optimize your crop nutrition management using our 12 scientifically-proven crop nutrient recommendation data profiles. With over 150 different crops in our database, we can help you create unique nutrition plans for whatever you’re growing. This digital solution for fertilization planning will help you maximize crop productivity and sustainably use your resources.

It’s also the first crop nutrition optimization planning tool that accounts for controlled-release fertilizers. Field agronomists can include these fertilizers in their crop nutrition management plans and see the nutritional distribution along the different phenological stages of the crop. This includes the expected depletion date of the controlled release fertilizer, so they can schedule the next fertilizer application at the optimum time.

The standardization of field-level agronomic practices helps with operational control, visibility, and unification across the growing season.