ABSTRACT Phytopathogenic diseases impact the development and yield of grapevines, resulting in economic, social and environmental losses. Sick plants have their metabolism changed, leading to alterations in their reflectance spectra. Little is known on these alterations, and a better knowledge could be used in the development of sensors able to detect diseases through fast, non-destructive techniques. This study was aimed at detecting spectral changes of grape leaves (Vitis vinifera cv. Cabernet Sauvignon), with early symptoms of downy mildew (Plasmopara viticola), powdery mildew (Uncinula necator), black-foot (Dactylonectria macrodidyma) and Petri disease (Phaeoacremonium spp.). Plants grown in pots and kept in a greenhouse were inoculated with the pathogens. In early stages of disease development, reflectance measurements were performed using a FieldSpec 3 spectroradiometer with leaf-clip attachment. The investigation began with discriminant analysis, which revealed that symptomatic plants are separated from the control ones. Reflectance spectra were, therefore, further investigated, looking for alterations on the shape of the spectra, characteristic of each disease. The disease descriptors were based on ratios between spectral features internal to a spectrum, a procedure which allowed the derivation of parameters intrinsic to each disease. A set of thresholds, defined as the ratios of reflectance at selected wavelengths, were derived for the studied diseases. For these ratios, the selected wavelengths (nm) were R443/R496, R443/R573, R443/R695, R443/R1900, R496/R573, R496/R695, R516/R1900 and R1900/R2435. The spectra from symptomatic plants present shape changes of as much as 20% with respect to healthy plants. The observed spectral changes are larger for black-foot and powdery mildew, but some wavelength ratios are also indicators of downy mildew and Petri disease. Data from wavelengths shorter than 700 nm in general carry more information than measurements at near infrared. These results are potentially useful to the development of low-cost devices to field use, providing real-time disease detection to early assessment of vineyard health status.
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