A Decision Support System for Vine Growers Based on a Bayesian Network

  • Philippe Abbal
  • , Jean Marie Sablayrolles
  • , Éric Matzner-Lober
  • , Jean Michel Boursiquot
  • , Cedric Baudrit
  • , Alain Carbonneau

Research output: Contribution to journalArticlepeer-review

Abstract

We propose here a decision support system for vine growers to assess the quality of a vineyard to be planted. The quality of a vineyard is defined by the probability of possible profitability of the wine sales he is able to produce. The model, based on a Bayesian network (BN), takes into account environment and the parameters defining vineyard status with their associated interactions. BN are widely used for knowledge representation and reasoning under uncertainty in natural resource management. There is a rising interest in BN as tools for ecological and agronomic modelling. Data were collected from knowledge of vine-growing experts. We developed a C# computer program predicting the likely quality of a vineyard. The model has been validated on existing vineyards with prediction ability around 75 %. This system should ease assessments of the likely impact of the choices and decisions of vine growers on the quality of new vineyards to be planted in any part of the world. No such model has been developed before for vine growers.

Original languageEnglish
Pages (from-to)131-151
Number of pages21
JournalJournal of Agricultural, Biological, and Environmental Statistics
Volume21
Issue number1
DOIs
Publication statusPublished - 1 Mar 2016
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 13 - Climate Action
    SDG 13 Climate Action

Keywords

  • Bayesian network
  • Climate change
  • Complex systems
  • Expert data
  • Vineyard quality

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