Source: AGRICULTURAL RESEARCH SERVICE submitted to
SURVEY OF COTTON CONTAMINATION AT THE GIN STAND FEEDER APRON IN MULTIPLE COMMERCIAL COTTON GINS
Sponsoring Institution
Agricultural Research Service/USDA
Project Status
ACTIVE
Funding Source
Reporting Frequency
Annual
Accession No.
0441368
Grant No.
(N/A)
Cumulative Award Amt.
(N/A)
Proposal No.
(N/A)
Multistate No.
(N/A)
Project Start Date
Jan 1, 2022
Project End Date
Dec 31, 2022
Grant Year
(N/A)
Program Code
[(N/A)]- (N/A)
Recipient Organization
AGRICULTURAL RESEARCH SERVICE
(N/A)
LUBBOCK,TX 79401
Performing Department
(N/A)
Non Technical Summary
(N/A)
Animal Health Component
100%
Research Effort Categories
Basic
0%
Applied
100%
Developmental
0%
Classification

Knowledge Area (KA)Subject of Investigation (SOI)Field of Science (FOS)Percent
2041710202050%
5111810202050%
Goals / Objectives
The global objective of the proposed research is to assess the best method for detecting plastic contamination at the gin-stand feeder apron and in the field. The specific objectives is to develop methods for detection of black plastic on the gin stand feeder apron, that will then be used to augment the incumbent's plastic inspection detection and ejection system, "PIDES". The new classifier will then be incorporated into the incumbent's PIDES software and then verification trials will be conducted using the laboratory based test equipment.
Project Methods
To help mitigate plastic contamination at the gin, a machine-vision detection and removal system was developed by the incumbent's that utilizes low-cost color cameras to see plastic coming down the gin-stand feeder apron, which upon detection, blows plastic out of the cotton stream to prevent contamination. The focus of this phase of the research is to develop classifier algorithms for detection of black plastic and then to incorporate these new algorithms into the PIDES software to enable real time detection and ejection of black plastic on a gin stand feeder apron. After incorporation of the algorithms into the software, laboratory test equipment will be used to assess the efficacy of the proposed algorithms, to assess it's suitability for real-world incorporation into the PIDES software in commercial deployments.