Theses and Dissertations

Issuing Body

Mississippi State University

Advisor

To, FIlip

Committee Member

Lowe, John W.

Committee Member

Du, Qian

Date of Degree

12-10-2021

Document Type

Graduate Thesis - Campus Access Only

Major

Biological Engineering

Degree Name

Master of Science (M.S.)

College

James Worth Bagley College of Engineering

Department

Department of Agricultural and Biological Engineering

Abstract

Plastic contamination in cotton is a problem in cotton industry and researchers have worked on this problem with different approaches. This thesis documents the design of mechanical and electronic real-time systems for detecting and removing plastic contaminants. The mechanical system was designed to expose plastic embedded inside the seed cotton to the sensor and to separate plastic contaminated cotton from the process stream. The detection system consisted of an embedded computer interfaced with a USB camera and Neural Network (NN) software running in it. Two NN models were tested, a transfer learning model and a built-from-scratch original model. The original NN model had better performance and accuracy than the transfer learning model. An accuracy 95% was achieved for classifying images containing plastic or not containing plastic with an original model. The plastic removal rate of the overall machine was 68%.

Sponsorship

USDA-ARS

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