Abstract
Crop plants are subjected to various biotic and abiotic stresses. Both root-knot nematodes (biotic stress) and water deficiency (abiotic stress) lead to similar drought symptoms in the plant canopy. In this work, hyperspectral imaging was used for early detection of nematode infestation and water deficiency (drought) stress in tomato plants. Hyperspectral data in the range from 400 to 2500 nm of plants subjected to different watering regimes and nematode infestation levels were analysed by partial least squares – discriminant analysis (PLS-DA) and partial least squares – support vector machine (PLS-SVM) classification. PLS-SVM classification achieved up to 100% accuracy differentiating between well-watered and water-deficient plants, and between 90 and 100% when identifying nematode-infested plants. Grouping the data according to the time of imaging increased the accuracy of classification. Shortwave infrared spectral regions associated with the OH and CH stretches were most relevant for the identification of nematode infested plants and severity of infestation. This study demonstrates the capability of hyperspectral imaging to identify and discriminate between biotic and abiotic plant stresses.
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