Application of Support Vector Machines to Melissopalynological Data for Honey Classification

Giovanna Aronne, Veronica De Micco and Mario R. Guarracino
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Giovanna Aronne: University of Naples Federico II, Italy
Veronica De Micco: University of Naples Federico II, Italy
Mario R. Guarracino: Italian National Research Council, Italy

International Journal of Agricultural and Environmental Information Systems (IJAEIS), 2010, vol. 1, issue 2, 85-94

Abstract: In this paper, the authors address the problem of the discrimination of geographical origin and the selection of marker species of honeys using Support Vector Machines and z-scores. The methodology is based on the elaboration of palynological data with statistical learning methodologies. This innovative solution provides a simple yet powerful tool to detect the origin of honey samples. In case of honeys from Sorrento Peninsula, the discrimination from other Italian honeys is obtained with high accuracy.

Date: 2010
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Persistent link: https://EconPapers.repec.org/RePEc:igg:jaeis0:v:1:y:2010:i:2:p:85-94

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