2025
Advanced Detection and Monitoring of Red Crown Rot in Illinois Soybean Fields Using Remote Sensing and Machine Learning
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Contributor/Checkoff:
Illinois Soybean Association
Category:
Sustainable Production
Keywords:
DiseasePest
Parent Project:
This is the first year of this project.
Lead Principal Investigator:
Boris Camiletti, University of Illinois at Urbana-Champaign
Co-Principal Investigators:
Project Code:
Contributing Organization (Checkoff):
Illinois Soybean Association
$10,756
Institution Funded:
University of Illinois at Urbana-Champaign
$10,756
Brief Project Summary:
The scope of this research proposal is to address the significant threat of Red Crown Rot (RCR) in Illinois soybean fields through the development and implementation of advanced technologies.
Information And Results
Project Summary

The scope of this research proposal is to address the significant threat of Red Crown Rot (RCR) in Illinois soybean fields through the development and implementation of advanced technologies.

Project Objectives

We aim to overcome the limitations of manual scouting by integrating remote sensing technologies and machine learning algorithms for comprehensive monitoring and early detection of RCR. Our approach leverages both drone and satellite imagery to analyze the spatial distribution of RCR within individual fields and across the state.

Project Deliverables

This represents the first steps towards a predictive model for RCR occurrence.

Progress Of Work

Final Project Results

Benefit To Soybean Farmers

Farmers will be able to detect hot spot in their fields and adjust management practices accondingly.

The United Soybean Research Retention policy will display final reports with the project once completed but working files will be purged after three years. And financial information after seven years. All pertinent information is in the final report or if you want more information, please contact the project lead at your state soybean organization or principal investigator listed on the project.