2019
Imaging and Foliar Tissue Sampling in Soybeans
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Contributor/Checkoff:
Ohio Soybean Council
Category:
Sustainable Production
Keywords:
Data analysisData Management
Parent Project:
This is the first year of this project.
Lead Principal Investigator:
John Fulton, Auburn University
Co-Principal Investigators:
Project Code:
19-R-19
Contributing Organization (Checkoff):
Ohio Soybean Council
$50,000
Institution Funded:
The Ohio State University
$50,000
Brief Project Summary:

The overarching goal of this project is to develop novel, small UAV-based, remote-sensing technologies for rapid diagnoses of soybean crop health based on machine learning and cutting-edge image acquisition techniques. An allied tissue remote sampling approach developed in parallel will bolster confidence in machine learning for crop stress diagnosis and support prescriptive management of crop health. The project aims to design, prototype and test a small UAV attachment for foliar tissue sampling, continue to build and expand the library of high-resolution imagery for soybean crop health diagnosis, refine and improve computational processes and algorithms for image classification, conduct field-scale testing and use it to refine and improve algorithm user-friendliness.

Key Benefactors:
farmers, agronomists, extension agents

Information And Results
Project Deliverables

1) quick turnaround time for soybean crop health diagnostics; 2) potential use as an educational tool during grower meetings showing digital images of insect, disease, and nutrient damage; and 3) expanded in-service training opportunities for county educators.

Final Project Results

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.