Background:
In Central Iowa, growers have increasingly been shifting to earlier planting dates, driven by a consistent trend of improved yield potential. While this strategy has delivered performance gains, it has also introduced new agronomic risks—particularly from early-season cold stress.
One Iowa grower followed this early planting trend with corn going in the ground on April 11. However, multiple cold nights shortly afterward introduced considerable physiological stress to the young crop. With a history of weather-related challenges during early development stages, there was growing interest in identifying data-backed strategies to protect yield potential under such conditions.
Challenge:
By mid-May, AGMRI’s stress detection tools indicated that approximately 50% of the grower’s field was under stress attributed to cool weather and rainfall. Projections showed a potential yield loss of around 12 bushels per acre if no action was taken.
The grower faced uncertainty about whether a fungicide application so early in the season—especially post-herbicide—would effectively mitigate the issue. There was a hesitation to act without clear validation that an intervention would make a difference. AGMRI’s layered data and visualizations provided the necessary clarity to evaluate and act on the situation with confidence.
Solution:
Using AGMRI, fields that had endured three or more cold nights were identified for targeted fungicide applications.
Informed by this insight, the grower made a data-driven decision to apply a fungicide on May 18, which was precisely aligned with the peak stress period identified by AGMRI. This approach enabled the timely treatment of areas most affected by early cold exposure.
Results:
The impact was clear. Following the application, stress levels across the field dropped sharply—from 50% to 17%. The estimated 12-bushel yield loss was largely avoided, validating the value of making precision decisions based on AGMRI analytics.
Moving forward, this Iowa grower plans to incorporate AGMRI data as a standard tool in evaluating early-season fungicide use, particularly in seasons with early planting and fluctuating spring temperatures. The experience reinforced the benefit of pairing field-level insights with adaptive management to improve both productivity and efficiency.
“This kind of visibility changed how we respond to weather stress. We now prioritize action based on data, not just timing,” shared the grower.
