Early detection of phytophthora in potato plants using hyperspectral imaging

An important primary inoculum source of Phytophthora infestans are latent infected seed potatoes. To remove those sources before symptom expression, it is necessary to detect those before symptom expression. Often, when a human can detect it by eye, sporulation has occurred, moreover it is not feasible to check all potato plants by hand. It is possible to detect a P. infestans infection early, using hyperspectral imaging. However, models trained on the spectral information only, do not generalize, because the spectrum is very much dependent on the local conditions like soil humidity. A method is developed to detect phytophthora early by comparing spectra from infected plants with the spectra of healthy plants that have grown under similar conditions, i.e., in the same row, and creating an image that quantifies deviations. On those images in turn a convolutional neural network is trained, which is able to detect infections on plants grown in another field or a year later in a similar manner but under different conditions