This thesis explored two aspects of sensing and imaging applied in plant pathology. In a bibliometric study, science mapping was applied to mine journal and proceedings publications from the past three decades on the topic of sensing and imaging of plant disease to illuminate research habits, publication trends, and collaboration patterns and provide a baseline for future research on scientific networks in this interdisciplinary domain. In a 2-year field trial, UAV-based multispectral imaging was applied to detect symptoms of the recently introduced cotton leafroll dwarf virus (CLRDV) in eight cotton cultivars grown near Tifton, GA. Despite low symptom incidence, meaningful correlations were observed in 2020 between early-season leaf reddening and both the incidence of PCR-positive plants and the reflectance values obtained with the Normalized Pigment Chlorophyll Index (NPCI). Other relationships, such as those involving leaf drooping symptoms, the incidence of PCR-positive plants, and cotton lint yield remained elusive.