Theses and Dissertations

Issuing Body

Mississippi State University


Younan, Nicholas

Committee Member

Thomasson, J. Alex

Committee Member

Moorhead, Robert J.

Date of Degree


Document Type

Graduate Thesis - Open Access


Electrical Engineering

Degree Name

Master of Science


College of Engineering


Department of Electrical and Computer Engineering


A study of the soil characteristics, weather conditions, and effect of management skills on the yield of the agricultural crop requires site-specific details, which involves large amount of labor and resources, compared to the traditional whole field based analysis. This thesis discusses the design and implemention of yield monitor for sweetpotatoes grown in heavy clay soil. A data acquisition system is built and image segmentation algorithms are implemented. The system performed with an R-Square value of 0.80 in estimating the yield. The other main contribution of this thesis is to investigate the effectiveness of statistical methods and neural networks to correlate image-based size and shape to the grade and weight of the sweetpotatoes. An R-Square value of 0.88 and 0.63 are obtained for weight and grade estimations respectively using neural networks. This performance is better compared to statistical methods with an R-Square value of 0.84 weight analysis and 0.61 in grade estimation.



Machine Vision||Classification||Neural Networks||Image Segmentation||Yield Monitoring