Dr. Katie Gold’s Grape Sensing, Pathology, and Extension Lab at Cornell University (GrapeSPEC) studies the fundamental and applied science of plant disease sensing to improve sustainable integrated disease management. We specialize in in situ and imaging spectroscopy (aka “hyperspectral imaging,”) deployed at a range of spatial scales, from autonomous vineyard robots to spacecraft, to characterize disease physiology and the impacts of management intervention on early disease detection. The Gold Lab is the only group worldwide wholly dedicated to studying plant disease sensing. Our research combines plant pathology, machine learning, and remote sensing to improve early detection and sustainable management intervention. Plant pathology’s foundational theory is the disease triangle, or the concept that disease results from interactions of a virulent pathogen with a susceptible host within a conducive environment. Our interpretation adds a fourth element—management— and acknowledges that these interactions take place in human-modified environments. By studying plant disease sensing within this foundational framework, we trailblaze a new frontier that better harnesses time through earliest detection and management intervention to prevent crop loss and food insecurity. Often times the greatest challenge in disease management is simply finding it in the first place. We envision a world where advances in digital agriculture, remote sensing, and decision support make this a thing of the past. Our ongoing research includes building a framework for global disease surveillance (NASA-#80NSSC20K1533), asymptomatic viral disease detection (NASA-#80NSSC21K1605), building remote sensing decision support tools (USDA-2022-68006-36148), biotic-biotic stress differentiation, and plant protection sensing. These studies, and the future avenues they will lead to, will yield powerful insights into the changing climate’s impact on global disease patterns, improved security for the world’s most at-risk crops and wellbeing of the people that rely on them, and more mechanistic surveillance systems adaptive to not only pathosystem, but also specific genotype-environment-microbe-management combinations.
To read more about plant disease sensing, read our recent perspective piece in mSystems: https://journals.asm.org/doi/10.1128/mSystems.01228-21.