2022
Using Multispectral Platforms to Manage the Soybean Cyst Nematode
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Contributor/Checkoff:
Illinois Soybean Association
Category:
Sustainable Production
Keywords:
Crop protectionDiseaseField management
Parent Project:
Using multispectral platforms to manage soybean cyst nematode
Lead Principal Investigator:
Jason Bond, Southern Illinois University at Carbondale
Co-Principal Investigators:
Project Code:
Contributing Organization (Checkoff):
Illinois Soybean Association
$65,000
Institution Funded:
Southern Illinois University
$65,000
Brief Project Summary:
The project explores the use of multi-spectral imaging and modeling using remote sensing for detecting soybean cyst nematode stresses in crop fields. Using unmanned aerial vehicles (UAVs), the research team will collect images to find accurate imagery across light spectrums that can identify plant symptoms unique to SCN. The imagery can help researchers and farmers learn of plant physical stress and call attention to problems in a field that may be missed by scouting. The team will develop a workflow to speed up image stitching and to separate spectral image indices so they can focus on image analysis.
Key Beneficiaries:
#agronomists, #farmers, #nematologists, #pathologists
Unique Keywords:
#drones, #remote sensing, #scn, #soybean cyst nematodes, #soybean diseases
Information And Results
Project Summary

Our main goal is to develop a UAS-based artificial intelligence (AI) toolkit to detect soybean cyst nematode (SCN) related stresses of soybean. In the first seven months of the project funded last year, we have been developing a UAS-based remote sensing predictive modeling tool to determine SCN population density and its impact on soybean health.

Project Objectives

Field trials will be established at multiple locations in Illinois to collect multispectral and hyperspectral imagery of plant stress caused by SCN as well as SCN egg counts. These locations will serve as data generators for testing and improving the predictive models developed in 2021.

Project Deliverables

We will disseminate our research findings through conference presentations, extension publications, journal articles, and media releases to the precision farming industry and crop consultants. We will work with the Soybean Research Information Initiative (SRII) and the Crop Protection Network to publish updates and release information on the availability of the toolkit to a broader farming community for potential adoption. In addition, we will use social media like Facebook to share project information and progress. The proposed toolkit will be freely released via GitHub, a web-based computer algorithm sharing system so that the feedback can make improvements from precision agricultural research communities.

Progress Of Work

Final Project Results

Benefit To Soybean Farmers

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.