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

Journal: Horticulture research
Published Date: Dec 29, 2023

Abstract

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°C 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.

Authors

  • Hongrui Wang
    School of Integrative Plant Science, Horticulture Section, Cornell AgriTech, Cornell University, Geneva, NY 14456, USA.
  • Gaurav D Moghe
    School of Integrative Plant Science, Plant Biology Section, Cornell University, Ithaca, NY 14850, USA.
  • Al P Kovaleski
    Plant and Agroecosystem Sciences Department, University of Wisconsin-Madison, Madison, WI 53706, USA.
  • Markus Keller
    Department of Viticulture and Enology, Irrigated Agriculture Research and Extension Center, Washington State University, Prosser, WA 99350, USA.
  • Timothy E Martinson
    School of Integrative Plant Science, Horticulture Section, Cornell AgriTech, Cornell University, Geneva, NY 14456, USA.
  • A Harrison Wright
    Kentville Research and Development Centre, Agriculture and Agri-Food Canada, Kentville, Nova Scotia, B4N 1J5, Canada.
  • Jeffrey L Franklin
    Kentville Research and Development Centre, Agriculture and Agri-Food Canada, Kentville, Nova Scotia, B4N 1J5, Canada.
  • Andréanne Hébert-Haché
    Centre de Recherche Agroalimentaire de Mirabel, Mirabel, Québec, J7N 2X8, Canada.
  • Caroline Provost
    Centre de Recherche Agroalimentaire de Mirabel, Mirabel, Québec, J7N 2X8, Canada.
  • Michael Reinke
    Southwest Michigan Research and Extension Center, Michigan State University, Benton Harbor, MI 49022, USA.
  • Amaya Atucha
    Plant and Agroecosystem Sciences Department, University of Wisconsin-Madison, Madison, WI 53706, USA.
  • Michael G North
    Plant and Agroecosystem Sciences Department, University of Wisconsin-Madison, Madison, WI 53706, USA.
  • Jennifer P Russo
    School of Integrative Plant Science, Horticulture Section, Cornell AgriTech, Cornell University, Geneva, NY 14456, USA.
  • Pierre Helwi
    Martell & Co., 7 place Edouard Martell, Cognac 16100, France.
  • Michela Centinari
    Department of Plant Science, The Pennsylvania State University, University Park, PA 16802, USA.
  • Jason P Londo
    School of Integrative Plant Science, Horticulture Section, Cornell AgriTech, Cornell University, Geneva, NY 14456, USA.

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