Like Finding a Needle in a Haystack with AGMRI Disease Detection

A corn and soybean grower in Central Indiana partnered with his local cooperative for seed and chemical solutions in July 2023. The season had a dry start, and the grower was considering avoiding fungicide applications on his corn-after-corn field. In this area, diseases like tar spot can lead to yield losses of 5-25 bushels per acre or more, if left untreated.


The grower subscribed to AGMRI for the past two years and was familiar with the thermal feature to monitor for disease risk. In 2023, the grower was concerned about the potential for tar spot living in corn residue in several of his fields. Detecting disease potential in a vast field had been challenging in the past, so the grower examined the AGMRI thermal map to look for an increase in temperature or any hotspots to explore. Quickly he realized the thermal map indicated there might be disease present on the southeast part of a field. A scout was deployed to ground truth the area to determine whether to apply a fungicide. AGMRI directed the scout to the exact location in the field that showed potential for disease and indeed the scout found early signs of tar spot.

The AGMRI thermal layer revealed disease hotspots, enabling timely scouting and disease risk mitigation through a fungicide application. Post fungicide application, the thermal map showed a cooler stand. And, by digging deeper into the AGMRI historical yield map, it showed this area may have suffered from disease in the past.

The timely application of fungicide was made possible by AGMRI data, indicating where and when the disease started. This proactive approach helped the grower and local cooperative preserve crop health and potentially avoid significant yield losses. The experience underscored the value of AGMRI in optimizing disease management decisions at the right time of the season.


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Yield Forecast

Understand where your corn yield is based on the current state of the crop. As the season unfolds, see how it is having an impact on your final yield.

Yield Loss

Powered by years of Nitrogen research at the University of Missouri, our corn Yield Loss analytic, powered by NVision Ag, gives insight into potential yield loss due to Nitrogen deficiency. Optional analytic for nitrogen management.

Variable Dry Down

variable dry down

Understand which fields and which areas of the field are drying down to help plan your harvest logistics.

Underperforming Area

low crop health

Not all areas of your fields perform the same and low NDVI doesn’t necessarily mean there is anything you can do to fix it this year. Underperforming Area alerts you to the fields and areas of the fields that are performing below their historical potential. This will allow you to quickly find those fields and areas and make adjustments to get them back on target and protect yield.

Nutrient Deficiency

nutrient deficiency

As the crop grows, it can tell us more of what is wrong with it. This analytic finds the fields and areas of the fields where there is a nutrient deficiency so that issues can be addressed before grain fill.

Disease Stress

disease risk

In conjunction with the Thermal Stress, Disease Stress alert takes into account weather information to more precisely indicate the type of stress impacting the crop.

Thermal Stress

thermal risk

Using our thermal imagery, AGMRI can detect elevated heat patterns of the crop that indicate crop stress.

Crop Health

Crop Health

Get a complete view of your farms and fields and identify where yield potential is ranked highest to the lowest.

Weed Map & Weed Escape

weed escape

Know what fields and areas of the fields have weeds. With machine integration or based on planting date, be alerted to what fields have weeds that may be impacting yield.

Historical Field Performance

AGMRI creates 5 performance zones in each field based on the historical average of those zones. This data is used to compare the current season to help understand where you are underperforming from the zone potential.

Low Emergence

low emergence

Notification of what fields and areas of the field have poor emergence.

Stand Assessment

strand assessment

AGMRI detects the established rows and uses computer vision and machine learning to determine the best segment of row and compares the rest of the field to that segment to give you a relative map. If machine data is integrated, a stand population map is returned.