Date of Award:
Master of Science (MS)
Plants, Soils, and Climate
John G. Carman
The Citrus fruit industry in the United States has been affected during the last two decades because of the outbreak of the citrus greening disease, also known as Huanglongbing (HLB). Many people and organizations are working in therapeutics to help mitigate the impact of this disease, unfortunately there is not a cure yet. There are many mechanisms that needs to be understood about this disease, especially at the molecular level. Not only HLB, but many other infectious diseases are controlled by the interaction of proteins from the host (Citrus in this case) and from the pathogen that causes the disease. When these interactions occur, the normal activity of the plant host is altered and then the plant start to develop more and more ill severe symptoms.
The purpose of this research was to implement diverse computational methods to predict those interactions accurately. We applied several methods successfully used in other infectious diseases, and developed novel techniques including the Artificial Intelligence models. After a comprehensive analysis of our results, we identified some candidate genes that we believe are key HLB players which could be genetically modified to enhance resistance in Citrus plants.
The models developed from this study were implemented as web-based tools for real time use by the biologists and other stakeholders. The knowledge gained from this study can further be used to understand plant-pathogen interactions in other agricultural systems of economic importance.
Loaiza, Cristian D., "Computational Techniques for Elucidating Plant-Pathogen Interactions: A Case Study on Citrus-HLB Interactome" (2021). All Graduate Theses and Dissertations. 8164.
Available for download on Saturday, August 01, 2026
Copyright for this work is retained by the student. If you have any questions regarding the inclusion of this work in the Digital Commons, please email us at .