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myFSagronomy Agtrinsic Disease Modeling Program

August 13, 2025

Map of spornado traps in southwestern Ontario.

Article by Dale Cowan 
Agronomy Strategy Manager, Senior Agronomist
AGRIS Co-operative - Central Office


Predicting Foliar Disease Risk in Corn & Soybeans

When it comes to managing foliar fungal diseases in corn and soybeans, it all starts with the Disease Triangle:

  • Susceptible host – the crop plant (corn or soybeans)
  • Pathogen presence – fungal spores capable of causing disease
  • Favorable environmental conditions – weather that supports infection

When all three sides of this triangle align, the risk of infection is high. That’s when applying a fungicide can protect yield and grain quality.

How the Agtrinsic Disease Model Works

The Agtrinsic Disease Modeling Program combines cutting-edge spore detection with weather-based risk analysis to guide fungicide decisions.

  1. Spore Collection – Spornado Traps
    • Each trap collects airborne spores on a cassette (like a petri dish).
    • Cassettes are replaced weekly and sent to the Spornado lab in Toronto.
    • The lab runs DNA scans to identify and count specific disease-causing spores.
  2. Risk Index – Spore Counts + Weather Data
    • The system combines spore counts with field-specific weather conditions.
    • Results are shown as Disease Risk Days, indicating the likelihood of infection for each field.

Real-Time Disease Risk in Your Fields

Customers using the myFSagronomy app can view a field-by-field disease risk triangle during critical growth stages. This season, the model showed relatively low risk for both Tar Spot and Northern Corn Leaf Blight in most areas.

We also track risk across the entire territory, providing an overview of how many days the weather supported infection.

 

Ground-Truthing the Model

Since this is our first year testing the model, participating farmers who applied fungicide left a 350-foot untreated check strip in each test field. These strips, along with scouting reports, will help verify the model’s accuracy in predicting disease incidence and severity.

What’s Next?

Results from harvest will tell us how well the Agtrinsic Disease Model predicted real-world disease pressure. As we refine the tool, our goal is to give farmers accurate, field-specific disease risk data—helping you time fungicide applications for maximum yield protection and ROI.


Disclaimer: Some of the articles are generated by Growmark USA and may contain products and product recommendations not registered or available in Canada. 

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