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.