About Me

I am a fourth-year Ph.D. candidate studying at Texas A&M University. I graduated from Campbell University in Buies Creek, NC, in 2015 with a B.S. in Biological Sciences, minoring in Environmental Science. Prior to beginning my graduate career, I worked for Bayer Crop Science in the Soybean Pathology Lab.

I am studying the spatiotemporal dynamics of inoculum in two plant pathosystems: Fusarium wilt of cotton (Fusarium oxysporum f. sp. vasinfectum) and citrus Huanglongbing (Candidatus Liberibacter asiaticus). Specifically, my research focuses on quantifying inoculum density and modeling the movement of inoculum through space and time. Other research has focused on developing and utilizing novel methods for analyzing low altitude remote sensing data and modeling the epidemiology of grapevine virus.

In addition to my research, I have taken part in many extracurricular activities. I served on the Texas A&M Plant Breeding Symposium planning committee for the 2019 and 2020 symposia, serving as the committee chair for 2020. I have also served as a senator to the Graduate and Professional Student Government, as the Poster Sessions Coordinator for the 2019 Student Research Week, and as the president of the Plant Pathology and Microbiology Graduate Student Club.

Publications

Davis II, R. D., Greene, J. K., Dou, F., Jo, Y. K., and Chappell, T. M. 2020. A practical application of unsupervised learning for analyzing plant image data collected using unmanned aircraft systems. Agronomy. doi: 10.3390/agronomy10050633 

Conference Proceedings

Davis II, R., Isakeit, T., and Chappell, T. M. 2021. Design and Implementation of a Robust Metric to Quantify Soilborne Fusarium oxysporum f. sp. vasinfectum Race 4 Inoculum Density. Cotton Beltwide Conferences.

Davis II, R. D. and Chappell, T. M. 2020. A robust metric for the environmental quantification of Fusarium oxsyporum f. sp. vasinfectum race 4. Cotton Beltwide Conferences. Austin, TX.

Davis II, R. D., Jo, Y. K., and Chappell, T. M. 2019. Unsupervised learning for efficient detection of plant disease through low altitude remote sensing. American Phytopathology Society. Cleveland, OH.

Davis II, R. D., Jo, Y. K., and Chappell, T. M. 2019. Efficient utilization of low altitude remote sensing technology for crop phenotype estimation. Emerging Researcher National Conference. Washington, D. C.