Background
An Indiana crop consultant and farmer balances a busy career in sales, service, and farming while also enjoying family time with his three children. As a second-year AGMRI user, this farmer is dedicated to optimizing farming practices and improving what’s within his control to avoid yield losses. Last season, he faced challenges with seed prescriptions, which led to money being left on the table. With a mindset of improving YoY, he knew AGMRI was his way of improving his efficiency. It not only allows him to find issues but, more importantly, quantifies them into an ROI at the end of the season.
Challenge
The challenge for this farmer is detecting an issue before it’s too late, given his time constraints. During the 2024 season, significant nitrogen distribution issues arose across multiple fields on his farm. A rushed application led to soil compaction and uneven nitrogen distribution due to a malfunction in the 15-row applicator. In this case, he used aerial, NVision, and VEG map layers to interpret the nitrogen and compaction implications. Despite catching the problem early, wet conditions prevented timely intervention. If left unaddressed, this could result in substantial yield losses—an estimated 10 bushels per acre, equating to a potential $37 per acre loss across corn acres.
Solution
AGMRI tools, including NVision and aerial mapping, enabled the farmer to identify the distribution problem with the applicator. Acknowledging the need for improvement, he plans to either upgrade to a 17-knife applicator or increase the rates on the current setup to ensure more consistent applications. Once these improvements are made, he intends to use AGMRI for 2025 and beyond to keep a close eye on the progression until it is a proven fix. Additionally, he plans to implement processes for evaluating soil conditions to avoid unnecessary soil compaction, as it has proven costly in this example.
Results
The farmer is an AGMRI advocate, acknowledging its role in helping meet his crop plan. He also recognized the importance of learning from past mistakes, like previous planting rates leading to low emergence. Now, with insights gained from AGMRI, he will be in a better position to enhance nitrogen practices, seeding prescriptions, and overall crop health, including disease detection like tar spot. He will continue to leverage AGMRI to optimize operations in the future to improve efficiency and profitability.
