Application of Support Vector Machines to Melissopalynological Data for Honey Classification

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.