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Spectral signatures in the UV‐range can be combined with secondary plant metabolites by deep learning to characterise barley – powdery mildew interaction

  • Autor/in: Brugger, A., P. Schramowski, S. Paulus, U. Steiner, K. Kersting, A.-K. Mahlein
  • Jahr: 2021
  • Zeitschrift: Plant Pathology
  • Seite/n: doi: 10.1111/ppa.13411

Abstract

In recent studies, the potential of hyperspectral sensors for the analysis of plant-pathogen interactions was expanded to the ultraviolet range (UV; 200-380 nm) to monitor stress processes in plants. A hyperspectral imaging set-up was established to highlight the influence of early plant-pathogen interactions on secondary plant metabolites. In this study, the plant-pathogen interactions of three different barley lines inoculated with Blumeria graminis f.sp. hordei (Bgh, powdery mildew) were investigated. One susceptible genotype (cv. Ingrid, wild type) and two resistant genotypes (Pallas 01, Mla1 and Mla12 based resistance and Pallas 22, mlo5 based resistance) were used. During the first five days after inoculation (dai) the plant reflectance patterns were recorded and in parallel plant metabolites relevant in host-pathogen interaction were studied. Hyperspectral measurements in the UV-range revealed that a differentiation between barley genotypes inoculated with Bgh is possible and distinct reflectance patterns were recorded for each genotype. The extracted and analyzedanalysed pigments and flavonoids correlated with the spectral data recorded. A classification of non-inoculated and inoculated samples with deep learning revealed that a high performance can be achieved with self-attention networks. The subsequent feature importance identified wavelengths, which were most important for the classification, and these wavelengths were linked to pigments and flavonoids. Hyperspectral imaging in the UV-range allows for a characterisation of different resistance reactions, can be linked to changes of secondary plant metabolites with the advantage of being a non-invasive method and therefore enables a greater understanding of the plants' reaction to biotic stress as well as resistance reactions.
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