A. McElrone Lab & USDA
Viticulture and Enology
Modeling and Quantitative Horticulture, Water Relations, Crop Production, Remote Sensing, Machine Learning The overarching goal of my work is the improvement of plant research methods and technology through quantitative assessment and iterative enhancement. While the majority of my experience deals with in vitro methods, I am broadly interested in both model-plant and crop-plant research technologies. Within the topic of protocol improvement, my research focuses on augmenting the robustness of experiments via enhancing the accuracy, speed, and efficiency at the data collection and analysis stages. Currently, I am working with David Block’s lab to improve remote sensing technologies for estimating single grapevine water use. Through applications of software engineering, robotics, novel imaging methods, and integrated multi-step procedures, my work aims to achieve the goal of accelerating the pace of plant biology research while emphasizing reproducibility.