Original research articles

Precision viticulture data analysis using fuzzy inference systems


Aims: Various types of data are likely to be used in a precision viticulture framework, to adjust management actions according to within field variations. This paper proposes an alternative way of analysis to classical methods.

Methods and Results: Data are analysed using fuzzy logic techniques. The result is a set of linguistic fuzzy rules induced from data. In this paper, the rules are build in order to explain the relationship between vintage quality, reduced to sugar content, and other available variables. The resulting system is proved to be accurate, moreover thanks to fuzzy logic interpretability, the induced rules are analyzed and compared to expert knowledge.

Conclusion: This example highlights the potential of fuzzy logic to deal with precision viticulture datasets.

Significance and impact of study: This is a preliminary work, it has been carried out using a free software available in the internet.

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Mathieu Grelier

Affiliation : Comité Interprofessionnel du Vin de Champagne, 5 rue Henri Martin, 51200 Epernay, France

Serge Guillaume

Affiliation : Cemagref, UMR ITAP, F-34196 Montpellier, France


Bruno Tisseyre

Affiliation : UMR ITAP Montpellier SupAgro/Irstea, bat 21, 2 place Pierre Viala, 34060 Montpellier, France

Thibaut Scholasch

Affiliation : University of California, Berkeley, ESPM Department 151 Hilgard Hall, Berkeley, CA 94720-3110, United States