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Application of Support Vector Machines to Melissopalynological Data for Honey Classification

Application of Support Vector Machines to Melissopalynological Data for Honey Classification

Giovanna Aronne, Veronica De Micco, Mario R. Guarracino
Copyright: © 2010 |Volume: 1 |Issue: 2 |Pages: 10
ISSN: 1947-3192|EISSN: 1947-3206|EISBN13: 9781609609504|DOI: 10.4018/jaeis.2010070105
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MLA

Aronne, Giovanna, et al. "Application of Support Vector Machines to Melissopalynological Data for Honey Classification." IJAEIS vol.1, no.2 2010: pp.85-94. http://doi.org/10.4018/jaeis.2010070105

APA

Aronne, G., De Micco, V., & Guarracino, M. R. (2010). Application of Support Vector Machines to Melissopalynological Data for Honey Classification. International Journal of Agricultural and Environmental Information Systems (IJAEIS), 1(2), 85-94. http://doi.org/10.4018/jaeis.2010070105

Chicago

Aronne, Giovanna, Veronica De Micco, and Mario R. Guarracino. "Application of Support Vector Machines to Melissopalynological Data for Honey Classification," International Journal of Agricultural and Environmental Information Systems (IJAEIS) 1, no.2: 85-94. http://doi.org/10.4018/jaeis.2010070105

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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.

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