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Open Access

Peer-reviewed

Research Article

Forecasting severe grape downy mildew attacks using machine learning

Mathilde Chen ,

Roles Conceptualization, Formal analysis, Writing – original draft, Writing – review & editing

* E-mail: mathilde.chen@acta.asso.fr

Affiliation Inserm U1153, CRESS, Epidemiology of Ageing and Neurodegenerative diseases, Université de Paris, Paris, France

http://orcid.org/0000-0002-5982-2143

⨯
François Brun,

Roles Conceptualization, Validation

Affiliation ACTA, INRA, UMR AGIR, Castanet Tolosan, France
⨯
Marc Raynal,

Roles Conceptualization, Validation

Affiliation IFV, Bordeaux Nouvelle Aquitaine, UMT SEVEN, Villenave d’Ornon Cedex, France
⨯
David Makowski

Roles Conceptualization, Formal analysis, Validation, Writing – original draft, Writing – review & editing

Affiliations INRA, UMR Agronomie, AgroParisTech, Université Paris-Saclay, 78850 Thiverval Grignon, France, CIRED, 94130 Nogent-sur-Marne, France
⨯

Forecasting severe grape downy mildew attacks using machine learning

Mathilde Chen,
François Brun,
Marc Raynal,
David Makowski

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Published: March 12, 2020
https://doi.org/10.1371/journal.pone.0230254

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Fungicides
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Epidemiology
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Grapes
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Medical risk factors
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Leaves
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Downy mildew
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Machine learning
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