Automatic diagnosis of a multi-symptom grape vine disease using computer vision
dc.rights.license | open | en_US |
hal.structure.identifier | Laboratoire de l'intégration, du matériau au système [IMS] | |
dc.contributor.author | TARDIF, Malo | |
dc.contributor.author | AMRI, A. | |
hal.structure.identifier | Laboratoire de l'intégration, du matériau au système [IMS] | |
dc.contributor.author | KERESZTES, Barna
IDREF: 143373161 | |
hal.structure.identifier | Laboratoire de l'intégration, du matériau au système [IMS] | |
dc.contributor.author | DESHAYES, Aymeric | |
dc.contributor.author | MARTIN, D. | |
hal.structure.identifier | Ecophysiologie et Génomique Fonctionnelle de la Vigne [UMR EGFV] | |
dc.contributor.author | GREVEN, Marc | |
hal.structure.identifier | Laboratoire de l'intégration, du matériau au système [IMS] | |
dc.contributor.author | DA COSTA, Jean-Pierre
ORCID: 0000-0003-2390-0047 IDREF: 060561459 | |
dc.date.accessioned | 2024-02-22T14:53:50Z | |
dc.date.available | 2024-02-22T14:53:50Z | |
dc.date.issued | 2023-02 | |
dc.identifier.issn | 0567-7572 | en_US |
dc.identifier.uri | https://oskar-bordeaux.fr/handle/20.500.12278/188318 | |
dc.description.abstractEn | “Flavescence dorée” (FD) is a highly transmissible disease very closely monitored in Europe as it reduces vine productivity and causes vine death. Currently, this disease is controlled by a two-pronged approach: spray insecticide on a regular basis to kill the vector and by experts surveying each row in a vineyard. Unfortunately, these experts are not able to carry out such a task every year on every vineyard and need an aid for planning their surveys. In this study, we propose and evaluate an original automatic method for the detection of FD, based on computer vision and artificial intelligence applied to images acquired by proximal sensing. A two-step approach is used, mimicking expert’s scouting in the vine rows: i) the three known isolated symptoms are detected, ii) isolated detections are combined to make a diagnosis at vine scale. To achieve this, a detection deep neural network is used to detect and classify non-healthy leaves into three classes – ‘FD symptomatic leaf', ‘Esca leaf’ and ‘Confounding leaf’ – while a segmentation network retrieves FD symptomatic shoots and bunches. Finally, the association of the detected symptoms is performed by a RandomForest classifier allowing a diagnosis at the image scale. The experimental evaluation is conducted on images collected on 14 blocks planted with 5 grape cultivars, allowing the study of the impact of acquisition conditions and variability of symptom expressions among grape cultivars. © 2023 International Society for Horticultural Science. All rights reserved. | |
dc.language.iso | EN | en_US |
dc.subject.en | Flavescence dorée | |
dc.subject.en | Artificial intelligence | |
dc.subject.en | Deep learning | |
dc.subject.en | Image processing | |
dc.subject.en | Detection | |
dc.subject.en | Segmentation | |
dc.subject.en | Proximal sensing | |
dc.title.en | Automatic diagnosis of a multi-symptom grape vine disease using computer vision | |
dc.type | Article de revue | en_US |
dc.identifier.doi | 10.17660/ActaHortic.2023.1360.7 | en_US |
dc.subject.hal | Sciences du Vivant [q-bio]/Biologie végétale | en_US |
bordeaux.journal | Acta Horticulturae | en_US |
bordeaux.page | 53-60 | en_US |
bordeaux.volume | 1360 | en_US |
bordeaux.hal.laboratories | Ecophysiologie et Génomique Fonctionnelle de la Vigne (EGFV) - UMR 1287 | en_US |
bordeaux.institution | Université de Bordeaux | en_US |
bordeaux.institution | Bordeaux Sciences Agro | en_US |
bordeaux.institution | INRAE | en_US |
bordeaux.institution | Bordeaux INP | |
bordeaux.institution | CNRS | |
bordeaux.peerReviewed | oui | en_US |
bordeaux.inpress | non | en_US |
hal.identifier | hal-04473378 | |
hal.version | 1 | |
hal.date.transferred | 2024-02-22T14:53:52Z | |
hal.popular | non | en_US |
hal.audience | Internationale | en_US |
hal.export | true | |
dc.rights.cc | Pas de Licence CC | en_US |
bordeaux.COinS | ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Acta%20Horticulturae&rft.date=2023-02&rft.volume=1360&rft.spage=53-60&rft.epage=53-60&rft.eissn=0567-7572&rft.issn=0567-7572&rft.au=TARDIF,%20Malo&AMRI,%20A.&KERESZTES,%20Barna&DESHAYES,%20Aymeric&MARTIN,%20D.&rft.genre=article |
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