Background
AGMRI Predictive Disease flagged the season’s first confirmed tar spot in Indiana in early June, then narrowed roughly 90 at-risk fields into a scouting filter that uncovered the disease in five more counties—giving crop consultants a head start. Difficult weather at planting—cold and wet—led to rough emergence and reduced plant health across the region: the kind of stressed start that can set corn up for disease. It set the stage for something nobody expected this early— the first confirmed case of tar spot in Indiana. Tar spot is rarely on anyone’s radar in early June; in a typical year it isn’t found until late in the month, which made an early-June confirmation genuinely unusual.
Challenge
Finding tar spot early is hard. The first signs are tiny lesions on only a handful of plants, easy to miss—and no one can put scouts in every field checking every leaf. In a year when stressed corn and unusual weather raised the risk, the disease could establish and start spreading before anyone confirmed it was present, and once it’s spreading, the window closes fast (tar spot can cost on the order of 35 bu/ac in a bad year). The real challenge was knowing where to look—early, before the calendar said tar spot should be a concern.
Solution
Predictive Disease answered the hardest question first: where to look. Rather than blanket scouting, it produced a list of roughly 90 fields across Indiana where the combination of weather, hybrid, and tillage made conditions conducive to tar spot spore growth.
That list pointed scouts at the highest-risk fields first—and it’s how the season’s first confirmed Indiana case was found on June 9, in a single field the model flagged. The find didn’t just confirm one case; it validated the model and turned a list of at-risk fields into a working scouting plan for the rest of the season. The platform surfaced where to look; the scouting call and confirmation stayed with the agronomy team.
Results
Building on that first find, the crop consultants used Predictive Disease as a filter for scouting. Working from the list of at-risk fields, they confirmed tar spot in five additional counties—early. That head start mattered: it let consultants get ahead of disease-containment conversations with their growers rather than reacting after the disease had already taken hold. With the model validated by an early-season confirmation, the team can keep focusing limited boots-on-the-ground time on the fields most likely to need it.
