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Estimative of white mold severity in common bean crops using hyper and multispectral sensors

This study aimed to identify wavelengths and spectral ranges from hyper and multispectral reflectance using PLS regression; and to promote comparative evaluation of these methods and ten vegetation indices to determine those that best estimate levels of white mold severity in common beans. Experiments were implemented in the municipalities of Viçosa and Oratorios, Minas Gerais state. Hyperspectral reflectance measurements were acquired with the spectroradiometer, whose useful reading range was between 440 and 900 nm. Multispectral reflectance measurements were obtained from camera images comprising five bands (red, green, blue, red-edge and infrared). The indexes of disease severity were low. In Viçosa the average was 5.8% and in Oratorios, 7.4%. Mathematical models using hyperspectral reflectance performed better for estimating white mold. The red-edge band presented the wavelengths that best estimate the severity of white mold. Vegetation index resistant to the soil reflectance effects was better to estimate white mold than the other indices.

PLS regression; vegetation index; precision agriculture


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