Undergraduate researcher Maggie Marlino at work crafting a rack and columns for experimentation with soilborne inoculum.
Roy’s Citrus Greening Research
I recently started research focusing on citrus greening and inoculum density. In the left picture, Candidatus Liberibacter asiaticus (CLas), the presumed causal agent of citrus greening, was first detected 6 years ago. The right picture shows a more recent infection first detected in 2020. The damage from a long-term infection is apparent between the two pictures where there are fewer leaves and the difference in the color of the leaves.
Roy’s Sampling at the Citrus Center
I went to the Citrus Center in Weslaco, Texas, to set up data loggers and collect samples. Data loggers will be used to record soil and canopy temperatures. The data from these loggers will be interesting as they were set in place shortly before Winter Storm Uri, which is likely to have affected citrus trees.
Manjari’s work with artificial diets
Here is a cool image of a cotton aphid feeding on colored artificial diet — I am excited to use this system to study vectoring mechanisms.
Manjari’s EPG work
The following figures are from my poster entitled “Comparative electropenetrography of striped mealybug and cotton aphid on cotton,” presented at the 2020 conference of the Entomological Society of America.
Preliminary findings on feeding of striped mealybug and cotton aphid on cotton seedlings show characteristic waveform patterns of these two hemipterans.
Counting Fleahoppers
Manjari and Jensen counting cotton fleahopper nymphs collected daily from woolly croton as a part of a phenology study.
Roy’s LARS work
Roy’s collaboration with other researchers using unmanned aerial systems led to an application recently published in Agronomy. doi: 10.3390/agronomy10050633
Roy set out to make use of available low-altitude remote sensing data. Available data are often more useful than unavailable data, in practice.
Work led us to recognize that data generated through LARS are different from data generated by walking in a field with a ruler in two fundamental (that’s a pun) ways: first, LARS data aren’t calibrated in the way that ruler measurements are; second, LARS data points come in by the million at today’s image resolution, and no one with a ruler takes that many measurements. Convention is to calibrate LARS data against the ground in a way similar to how people do it with rulers: the ruler doesn’t allow you to differentiate the ground from your measurement target, so you classify plants vs. ground by another process, involving your recognition of patterns based on colors, shapes, and your heuristics. This process for LARS-based estimation can use global positioning systems, computer vision, or other things that have lots of potential.
Roy asked, can we estimate plant heights accurately without calibrating LARS data against the ground through other means? Can we apply a heuristic to the data after they’re collected and estimate plant heights without knowing which distance-from-the-drone recordings are for the ground vs. the plants? The answer is yes, so long as you have data of the type and quantity provided through LARS, and that answer is detailed in his paper. Roy is also good at making schematics – here’s one that shows how images, values, and interpretations correspond in his technique:
Roy Davis
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.
Manjari Mukherjee
I am a first year PhD student at Texas A&M University, having joined the Chappell lab in Spring 2020. I received my Bachelors degree from Institute of Chemical Technology, Mumbai (India), and have completed my Masters in Food Science from The Pennsylvania State University.
My primary interests lie in studying vectored plant diseases through the interplay of inoculum quantification and transmission, and how stressors might influence these dynamics. To begin with, I have gotten started with cotton as a host, and intend on establishing vector colonies soon.
Jensen Hayter
I am a PhD candidate in my third year at Texas A&M University. I have an undergraduate degree in microbiology from Brigham Young University.
The central theme of my work is the investigation of how specific abiotic factors, particularly temperature and moisture availability, affect the phenology of key pests and pathogens. Currently, I am working with collaborators in forensic entomology to develop simulation models used to study how different thermal landscape scenarios could impact blow fly development and the implications this has in forensic investigations. These models port easily to agriculture where I am interested in applying them to study arthropod vectors of plant pathogens.
Publications and Conference Activity
Hayter, JT., Chappell, TM. (2019). Projecting spatially heterogeneous thermal landscapes into the past to drive insect development models. North American Forensic Entomology Association Annual Conference, Indianapolis, IN.
Hayter, JT., Chappell, TM. (2018). Adapting Soil Moisture Models to Improve Epidemiological Modeling of Soilborne Plant Disease. Conference on Soilborne Plant Pathogens, Portland, OR.
Hayter, JT., Chappell, TM. (2018). Integrating Real-time Edaphics into Epidemic Models for Predicting Risk in Soilborne Pathogen Systems. International Congress on Plant Pathology, Boston, MA.