Location: National Peanut Research Laboratory
Project Number: 6044-21000-006-005-S
Project Type: Non-Assistance Cooperative Agreement
Start Date: Jun 25, 2022
End Date: Jun 25, 2025
Aflatoxin contamination is a recurring problem in the US peanut industry leading to millions of dollars to remove prior to consumption. Aflatoxin cost are incurred at all segments of the industry and mitigating this problem will improve the economic stability of the entire industry and lead to industry growth. Thus, the overall goal of this project is to conduct research toward improving peanut quality in peanut through various approaches. Specific objectives include: 1. Develop a remote-sensing-based approach for in-field aflatoxin hotspot prediction and management. 2. Evaluate a deep learning-assisted hyperspectral fluorescence imaging system for postharvest aflatoxin detection at the shelling plant so that contaminated peanut kernels may be identified and segregated rapidly and reliably.
The Cooperator will collaborate with ARS in conducting research to reduce aflatoxin. Specifically, the cooperators will work with ARS in the following approaches: 1) develop highly efficient mathematical models that predict areas in the field in which aflatoxin hotspots will occur, and 2) develop a prototype Deep Learning -assisted Hyperspectral fluorescence imaging technology for high throughput postharvest aflatoxin detection in peanut single kernels. The results of the various research components will be published in refereed journals, trade magazines, or extension articles, presented at professional and grower meetings. Information from the research will be integrated into standard peanut processing procedures.