Spectral signatures of sugar beet leaves for the detection and differentiation of diseases |
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Authors: | A-K Mahlein U Steiner H-W Dehne E-C Oerke |
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Institution: | (1) Institute of Crop Science and Resource Conservation (INRES)—Phytomedicine, University of Bonn, Nussallee 9, 53115 Bonn, Germany |
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Abstract: | This study examines the potential of hyperspectral sensor systems for the non-destructive detection and differentiation of
plant diseases. In particular, a comparison of three fungal leaf diseases of sugar beet was conducted in order to facilitate
a simplified and reproducible data analysis method for hyperspectral vegetation data. Reflectance spectra (400–1050 nm) of
leaves infected with the fungal pathogens Cercospora beticola, Erysiphe betae, and Uromyces betae causing Cercospora leaf spot, powdery mildew and rust, respectively, were recorded repeatedly during pathogenesis with a spectro-radiometer
and analyzed for disease-specific spectral signatures. Calculating the spectral difference and reflectance sensitivity for
each wavelength emphasized regions of high interest in the visible and near infrared region of the spectral signatures. The
best correlating spectral bands differed depending on the diseases. Spectral vegetation indices related to physiological parameters
were calculated and correlated to the severity of diseases. The spectral vegetation indices Normalised Difference Vegetation
Index (NDVI), Anthocyanin Reflectance Index (ARI) and modified Chlorophyll Absorption Integral (mCAI) differed in their ability
to assess the different diseases at an early stage of disease development, or even before first symptoms became visible. Results
suggested that a distinctive differentiation of the three sugar beet diseases using spectral vegetation indices is possible
using two or more indices in combination. |
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Keywords: | |
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