首页|NYUS.2:an automated machine learning prediction model for the large-scale real-time simulation of grapevine freezing tolerance in North America

NYUS.2:an automated machine learning prediction model for the large-scale real-time simulation of grapevine freezing tolerance in North America

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Accurate and real-time monitoring of grapevine freezing tolerance is crucial for the sustainability of the grape industry in cool climate viticultural regions.However,on-site data are limited due to the complexity of measurement.Current prediction models underperform under diverse climate conditions,which limits the large-scale deployment of these methods.We combined grapevine freezing tolerance data from multiple regions in North America and generated a predictive model based on hourly temperature-derived features and cultivar features using AutoGluon,an automated machine learning engine.Feature importance was quantified by AutoGluon and SHAP(SHapley Additive exPlanations)value.The final model was evaluated and compared with previous models for its performance under different climate conditions.The final model achieved an overall 1.36℃ root-mean-square error during model testing and outperformed two previous models using three test cultivars at all testing regions.Two feature importance quantification methods identified five shared essential features.Detailed analysis of the features indicates that the model has adequately extracted some biological mechanisms during training.The final model,named NYUS.2,was deployed along with two previous models as an R shiny-based application in the 2022-23 dormancy season,enabling large-scale and real-time simulation of grapevine freezing tolerance in North America for the first time.

Hongrui Wang、Gaurav D.Moghe、Al P.Kovaleski、Markus Keller、Timothy E.Martinson、A.Harrison Wright、Jeffrey L.Franklin、Andréanne Hébert-Haché、Caroline Provost、Michael Reinke、Amaya Atucha、Michael G.North、Jennifer P.Russo、Pierre Helwi、Michela Centinari、Jason P.Londo

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School of Integrative Plant Science,Horticulture Section,Cornell AgriTech,Cornell University,Geneva,NY 14456,USA

School of Integrative Plant Science,Plant Biology Section,Cornell University,Ithaca,NY 14850,USA

Plant and Agroecosystem Sciences Department,University of Wisconsin-Madison,Madison,WI 53706,USA

Department of Viticulture and Enology,Irrigated Agriculture Research and Extension Center,Washington State University,Prosser,WA 99350,USA

Kentville Research and Development Centre,Agriculture and Agri-Food Canada,Kentville,Nova Scotia,B4N 1J5,Canada

Centre de Recherche Agroalimentaire de Mirabel,Mirabel,Québec,J7N 2X8,Canada

Southwest Michigan Research and Extension Center,Michigan State University,Benton Harbor,MI 49022,USA

Martell & Co.,7 place Edouard Martell,Cognac 16100,France

Department of Plant Science,The Pennsylvania State University,University Park,PA 16802,USA

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Office of the Vice Chancellor for Research and Graduate Education at the University of Wisconsin-MadisonWisconsin Alumni Research FoundationUSDA ARS appropriated projectNew York Wine and Grape FoundationCornell University Federal Capacity Funds Grant ProgramWashington Wine Industry FoundationUSDA National Institute of Food and Agriculture(NIFA)Federal Appropriation under Projects PEN0 4794Canadian Agricultural Partnership(CAP)projectCanadian Grapevine Certification Network(CGCN)Grape Growers'Association of Nova Scotia(GGANS)AgriScience programcluster on behalf of Agriculture and Agri-Food Canada

1910-21220-006-00D7003432ASC-12 Wine Grape Cluster Activity 7

2024

10.1093/hr/uhad286

园艺研究(英文)

园艺研究(英文)

CSTPCD
ISSN：
年,卷(期)：2024.11(2)
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