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

Author

Listed:
  • Philippe Abbal

    (INRA, UMR 1083, Science for Oenology)

  • Jean-Marie Sablayrolles

    (INRA, UMR 1083, Science for Oenology)

  • Éric Matzner-Lober

    (Université de Rennes II, CS24, 307)

  • Jean-Michel Boursiquot

    (INRA-SupAgro UMR 1034, AGAP)

  • Cedric Baudrit

    (INRA – Institut de Mécanique et d’Ingénierie)

  • Alain Carbonneau

    (SupAgro)

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.

Suggested Citation

  • Philippe Abbal & Jean-Marie Sablayrolles & Éric Matzner-Lober & Jean-Michel Boursiquot & Cedric Baudrit & Alain Carbonneau, 2016. "A Decision Support System for Vine Growers Based on a Bayesian Network," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 21(1), pages 131-151, March.
    • Handle: RePEc:spr:jagbes:v:21:y:2016:i:1:d:10.1007_s13253-015-0233-2
    DOI: 10.1007/s13253-015-0233-2
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    References listed on IDEAS

    as
    1. Ragin, Charles C., 2000. "Fuzzy-Set Social Science," University of Chicago Press Economics Books, University of Chicago Press, edition 1, number 9780226702773.
    2. Uusitalo, Laura, 2007. "Advantages and challenges of Bayesian networks in environmental modelling," Ecological Modelling, Elsevier, vol. 203(3), pages 312-318.
    3. repec:ucp:bkecon:9780226702766 is not listed on IDEAS
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