Unlock True Value from Agricultural Data with - Agmatix

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. 

Unlock True Value from Agricultural Data with - Agmatix

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.