Location: Cotton Ginning Research
Project Number: 6066-41440-009-016-S
Project Type: Non-Assistance Cooperative Agreement
Start Date: May 1, 2024
End Date: Apr 30, 2027
Objective:
1. To develop annotated image libraries that support the development of machine learning (ML) and artificial intelligence (AI) tools for identifying in-field trash and contaminants.
2. The development of in-field trash training models.
3. Develop an understanding of the characterization and availability of cotton gin by-products for utilization as a bio-based manufacturing feedstock.
4. Develop technoeconomic models for cotton gin by-product utilization as a bio-based manufacturing feedstock.
Approach:
The Cooperator will employ student workers to work directly with the ARS Engineers to coordinate the annotation of image libraries and to develop updated information on the characterization and availability of cotton gin by-products. ARS Engineers will collaborate with graduate students whose research focus is on developing in-field trash training models and/or developing technoeconomic models. The Cooperator faculty members and a Geographic Information System(GIS) analyst will make sure that the team is actively and effectively communicating to achieve the project goals. Further, the GIS analyst will be working to develop out cloud based solutions to standardize and align various datasets that can be easily shared amongst the team members and comply with ARS data policies. It is expected that the Cooperator students will visit the ARS Stoneville Gin Lab multiple times to ensure project objectives and milestones are being met to build up a strong team environment with the hopes of bringing some of these engineering graduate students into ARS in the future.
