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 However, in the past, these trials were carried out in isolated environments using outdated on-prem trial systems.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.
You may be interested in:
Next Generation Field Trials are Data-Driven
Critical Factors Driving Trends in Field Trials Today
Boosting Agricultural Output: The Impact of Digital Transformation and Data Analysis in Field Trials
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.
