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An expertized grapevine disease image database including five grape varieties focused on Flavescence dorée and its confounding diseases, biotic and abiotic stresses
The grapevine is vulnerable to diseases, deficiencies, and pests, leading to significant yield losses. Current disease controls involve monitoring and spraying phytosanitary products at the vineyard block scale. However, automatic detection of disease symptoms could reduce the use of these products...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10294005/ https://www.ncbi.nlm.nih.gov/pubmed/37383825 http://dx.doi.org/10.1016/j.dib.2023.109230 |
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author | Tardif, Malo Amri, Ahmed Deshayes, Aymeric Greven, Marc Keresztes, Barna Fontaine, Gaël Sicaud, Laetitia Paulhac, Laetitia Bentejac, Sophie Da Costa, Jean-Pierre |
author_facet | Tardif, Malo Amri, Ahmed Deshayes, Aymeric Greven, Marc Keresztes, Barna Fontaine, Gaël Sicaud, Laetitia Paulhac, Laetitia Bentejac, Sophie Da Costa, Jean-Pierre |
author_sort | Tardif, Malo |
collection | PubMed |
description | The grapevine is vulnerable to diseases, deficiencies, and pests, leading to significant yield losses. Current disease controls involve monitoring and spraying phytosanitary products at the vineyard block scale. However, automatic detection of disease symptoms could reduce the use of these products and treat diseases before they spread. Flavescence dorée (FD), a highly infectious disease that causes significant yield losses, is only diagnosed by identifying symptoms on three grapevine organs: leaf, shoot, and bunch. Its diagnosis is carried out by scouting experts, as many other diseases and stresses, either biotic or abiotic, imply similar symptoms (but not all at the same time). These experts need a decision support tool to improve their scouting efficiency. To address this, a dataset of 1483 RGB images of grapevines affected by various diseases and stresses, including FD, was acquired by proximal sensing. The images were taken in the field at a distance of 1-2 meters to capture entire grapevines and an industrial flash was ensuring a constant luminance on the images regardless of the environmental circumstances. Images of 5 grape varieties (Cabernet sauvignon, Cabernet franc, Merlot, Ugni blanc and Sauvignon blanc) were acquired during 2 years (2020 and 2021). Two types of annotations were made: expert diagnosis at the grapevine scale in the field and symptom annotations at the leaf, shoot, and bunch levels on computer. On 744 images, the leaves were annotated and divided into three classes: ‘FD symptomatic leaves’, ‘Esca symptomatic leaves’, and ‘Confounding leaves’. Symptomatic bunches and shoots were, in addition of leaves, annotated on 110 images using bounding boxes and broken lines, respectively. Additionally, 128 segmentation masks were created to allow the detection of the symptomatic shoots and bunches by segmentation algorithms and compare the results to those of the detection algorithms. |
format | Online Article Text |
id | pubmed-10294005 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-102940052023-06-28 An expertized grapevine disease image database including five grape varieties focused on Flavescence dorée and its confounding diseases, biotic and abiotic stresses Tardif, Malo Amri, Ahmed Deshayes, Aymeric Greven, Marc Keresztes, Barna Fontaine, Gaël Sicaud, Laetitia Paulhac, Laetitia Bentejac, Sophie Da Costa, Jean-Pierre Data Brief Update Article The grapevine is vulnerable to diseases, deficiencies, and pests, leading to significant yield losses. Current disease controls involve monitoring and spraying phytosanitary products at the vineyard block scale. However, automatic detection of disease symptoms could reduce the use of these products and treat diseases before they spread. Flavescence dorée (FD), a highly infectious disease that causes significant yield losses, is only diagnosed by identifying symptoms on three grapevine organs: leaf, shoot, and bunch. Its diagnosis is carried out by scouting experts, as many other diseases and stresses, either biotic or abiotic, imply similar symptoms (but not all at the same time). These experts need a decision support tool to improve their scouting efficiency. To address this, a dataset of 1483 RGB images of grapevines affected by various diseases and stresses, including FD, was acquired by proximal sensing. The images were taken in the field at a distance of 1-2 meters to capture entire grapevines and an industrial flash was ensuring a constant luminance on the images regardless of the environmental circumstances. Images of 5 grape varieties (Cabernet sauvignon, Cabernet franc, Merlot, Ugni blanc and Sauvignon blanc) were acquired during 2 years (2020 and 2021). Two types of annotations were made: expert diagnosis at the grapevine scale in the field and symptom annotations at the leaf, shoot, and bunch levels on computer. On 744 images, the leaves were annotated and divided into three classes: ‘FD symptomatic leaves’, ‘Esca symptomatic leaves’, and ‘Confounding leaves’. Symptomatic bunches and shoots were, in addition of leaves, annotated on 110 images using bounding boxes and broken lines, respectively. Additionally, 128 segmentation masks were created to allow the detection of the symptomatic shoots and bunches by segmentation algorithms and compare the results to those of the detection algorithms. Elsevier 2023-05-12 /pmc/articles/PMC10294005/ /pubmed/37383825 http://dx.doi.org/10.1016/j.dib.2023.109230 Text en © 2023 The Authors. Published by Elsevier Inc. https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Update Article Tardif, Malo Amri, Ahmed Deshayes, Aymeric Greven, Marc Keresztes, Barna Fontaine, Gaël Sicaud, Laetitia Paulhac, Laetitia Bentejac, Sophie Da Costa, Jean-Pierre An expertized grapevine disease image database including five grape varieties focused on Flavescence dorée and its confounding diseases, biotic and abiotic stresses |
title | An expertized grapevine disease image database including five grape varieties focused on Flavescence dorée and its confounding diseases, biotic and abiotic stresses |
title_full | An expertized grapevine disease image database including five grape varieties focused on Flavescence dorée and its confounding diseases, biotic and abiotic stresses |
title_fullStr | An expertized grapevine disease image database including five grape varieties focused on Flavescence dorée and its confounding diseases, biotic and abiotic stresses |
title_full_unstemmed | An expertized grapevine disease image database including five grape varieties focused on Flavescence dorée and its confounding diseases, biotic and abiotic stresses |
title_short | An expertized grapevine disease image database including five grape varieties focused on Flavescence dorée and its confounding diseases, biotic and abiotic stresses |
title_sort | expertized grapevine disease image database including five grape varieties focused on flavescence dorée and its confounding diseases, biotic and abiotic stresses |
topic | Update Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10294005/ https://www.ncbi.nlm.nih.gov/pubmed/37383825 http://dx.doi.org/10.1016/j.dib.2023.109230 |
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