Date of Award
12-2025
Document Type
Thesis
Degree Name
Master of Science (MS)
Department
Plant and Environmental Science
Committee Chair/Advisor
Dr. Christopher Saski
Committee Member
Dr. Jeffery Adelberg
Committee Member
Dr. Hudson Smith
Abstract
Fusarium oxysporum race 4 (FOV4) is a fungal pathogen that infects cotton (Gossypium spp.) plants, resulting in fusarium wilt (FW) disease that causes significant wilting, yield loss, and eventually death. Since cotton is such an important crop globally, with tens of millions of bales of fiber produced and sold worldwide each year, it is critical to develop effective strategies to combat this pathogen. This research aims to achieve that goal through two projects: (i) develop an efficient co-culture system to test fungal treatments in vitro, and (ii) develop a computer vision pipeline to more accurately assess plant resistance through quantifying fusarium wilt induced stem staining.
The goal of these projects is to provide breeders and researchers with tools that enable faster, easier development of cultivars and treatments to combat Fusarium wilt and protect global cotton production. These efforts will significantly advance FOV4 management in cotton and lay a foundation for future work in this area. Ultimately, however, the co-culture system did not distinguish between resistant and susceptible genotypes, as both produced similarly diseased seedlings. This is likely because the liquid culture conditions were overly favorable for FOV4, generating such high fungal pressure that even the resistant genotype was overwhelmed. Despite this limitation, the system remains a valuable in vitro platform for other applications, such as salinity or nutrient response assays. In contrast, our computer vision (CV) model performed exceptionally well. It achieved an accuracy of 0.998, a mean validation Dice coefficient of 0.82, and an F1 score of 0.96, with a mean absolute error (MAE) of 1.56 and a total runtime of one hour for 274 test images. These metrics indicate that the model is highly accurate, precise, and high throughput compared with manual, visual phenotyping.
Recommended Citation
Rylands, Thomas, "The Development of Tools for the Production of Fusarium Oxysporum Race 4 Resistant Cotton Varieties" (2025). All Theses. 4664.
https://open.clemson.edu/all_theses/4664