Committee Chair

Wang, Jin

Committee Member

Le, Thien; Ma, Ziwei; Wang, Xiunan

Department

Dept. of Mathematics

College

College of Arts and Sciences

Publisher

University of Tennessee at Chattanooga

Place of Publication

Chattanooga (Tenn.)

Abstract

Frogeye Leaf Spot (FLS), caused by Cercospora sojina, poses a significant threat to soybean production, with yield losses of 30 - 60%. Traditional mass-action models assume homogeneous mixing, which rarely holds in real fields and limits their ability to gain insights into FLS management. To address this, we developed a network-based model that incorporates real-field structure to improve FLS management in soybeans. Using Approximate Bayesian Computation, we estimated key epidemiological parameters and found that infection origin can shift the balance between transmission routes. Data analyses indicated that tillage and non-tillage plots did not differ significantly in fungal spread, decay, or disease severity. Finally, we show that early, targeted roguing is more effective than delayed or random removal. Together, these findings offer science-based guidance for FLS management and highlight the value of network-based models to inform agricultural disease control.

Acknowledgments

I am extremely grateful for the support and guidance provided by many individuals during the preparation of this thesis. Dr. Jin Wang and Dr. Thien Le, my advisors, were generous in mentoring, insightful in questions, and steady in encouragement; their high standards and clear direction shaped every stage of this research. In addition to thanking my committee members, Dr. Ziwei Ma and Dr. Xiunan Wang, for their thoughtful review and constructive feedback, which helped strengthen the clarity and rigor of this thesis. In addition to providing me with a rigorous academic environment, the Department of Mathematics at the University of Tennessee at Chattanooga also provided the resources necessary to complete this research. Finally, I wish to express my sincere appreciation for the patience and unwavering support of my family and friends.

Degree

M. S.; A thesis submitted to the faculty of the University of Tennessee at Chattanooga in partial fulfillment of the requirements of the degree of Master of Science.

Date

12-2025

Subject

Cercospora; Plant diseases--Epidemiology--Mathematical models; Soybean--Diseases and pests--Control

Keyword

Network-Modeling; Epidemiology; Approximate Bayesian Computation; Frogeye Leaf Spot; Soybean; Interventions

Document Type

Masters theses

DCMI Type

Text

Extent

xi, 70 leaves

Language

English

Rights

http://rightsstatements.org/vocab/InC/1.0/

License

http://creativecommons.org/licenses/by/4.0/

Date Available

1-1-2027

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Available for download on Friday, January 01, 2027

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