Pipeline for imaging, extraction, pre-processing, and processing of time-series hyperspectral data for discriminating drought stress origin in tomatoes.

Crop infestation with root-knot nematodes (RKN) and water deficiency lead to similar visible symptoms in the plant canopy. Identification of biotic or abiotic stress origin is therefore a problem, and currently the only reliable methods for determination of RKN infestation are invasive and applicable only for point-searches. In this study the applicability of hyperspectral remote sensing for early identification of drought stress and RKN infestations in tomato plants was tested. A four-stage image and data management pipeline was established: (1) image acquisition, (2) data extraction, (3) pre-processing, and (4) processing.