I am a PhD candidate in the Pathoview project, a collaboration between Utrecht University, TU Delft and plant breeders. In this project we are exploring how non-invasive sensors can be used to visualize, track and quantify plant disease.
We are interested in this because plant disease detection and quantification, or plant disease phenotyping, can contribute to reducing the application of pesticides. For example, plant breeders breed disease resistant crop varieties that don’t need chemical protection. But for selecting the most resistant plant genotypes they rely on accurate disease quantification. And if resistant crop varieties are not available, disease detection and monitoring in the field can support farmers in optimizing and minimizing pesticide applications. Traditionally, plant disease phenotyping is based on visual assessment of the disease symptoms. But the adoption of sensors, like diverse types of cameras, promises several advantages. Sensors may increase accuracy as well as throughput, and can detect signals beyond human perception, for example microscopic changes or in wavelength ranges outside the visible spectrum. Taking advantage of the expertise in imaging sensors at TU Delft and our knowledge of the physiological and biochemical processes underlying disease progress and symptom development, we aim to develop methods to efficiently detect and quantify plant disease.