Spectral signatures of sugar beet leaves for the detection and differentiation of diseases

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The potential of automatic methods of classification to identify leaf diseases from multispectral images (2011, unknown): “The plant cultivation and inoculation strategy is described in detail in Mahlein et al. (2010).”
HyperART: non-invasive quantification of leaf traits using hyperspectral absorption-reflectance-transmittance imaging (2015, background): “For instance, by using reflectance data, chlorophyll content of Arabidopsis thaliana [8] and disease symptoms’ incidence of Beta vulgaris [9-13] were recently monitored.”
High-Throughput Field-Phenotyping Tools for Plant Breeding and Precision Agriculture (2019, background): “This would call for combination of different spectral wavelengths and vegetation indices to make this distinction [20].”