Hyperspectral images of grapevine leaves including healthy leaves and leaves with biotic and abiotic symptoms
2023
Ryckewaert, Maxime | Heran, Daphné | Trani, Jean-Philippe | Mas Garcia, Sílvia | Feilhes, Carole | Prezman, Fanny | Serrano, Eric | Bendoula, Ryad | Technologies et Méthodes pour les Agricultures de demain (UMR ITAP) ; Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Montpellier ; Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro) | Scientific Data Management (ZENITH) ; Centre Inria d'Université Côte d'Azur (CRISAM) ; Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier (LIRMM) ; Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM) | Institut Français de la Vigne et du Vin [Siège] (IFV) | This work was supported by the INTERREG SUDOE SOE3/P2/E0911 Viniot project.
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Show more [+] Less [-]English. A hyperspectral imaging database was collected on two hundred and five grape plant leaves. Leaves were measured with a hyperspectral camera in the visible/near infrared spectral range under controlled conditions. This dataset contains hyperspectral acquisition of grape leaves of seven different varieties. For each variety, acquisitions were performed on healthy leaves and leaves with foliar symptoms caused by different grapevine diseases showing clear symptoms of biotic or abiotic stress on other organs. For each leaf, chemical measurements such as chlorophyll and flavonol contents were also performed.
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