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47 2008

Journal of Food and Nutrition Research
Súhrny čísla 4 / 2008

KRUŽLICOVÁ, D. - MOCÁK, J. - KATSOYANNOS, E. - LANKMAYR, E.
Classification and characterization of olive oils by UV-Vis absorption spectrometry and sensorial analysis
Journal of Food and Nutrition Research, 47, 2008, č. 4, s. 181-188

Ján Mocák, Department of Chemistry, Faculty of Natural Sciences, University of Ss. Cyril & Methodius, Nám. J. Herdu 2, SK – 91701 Trnava, Slovakia. E-mail: jan.mocak@ucm.sk

Súhrn: A number of 193 olive oil samples of five different olive oil types and three different locations of origin have been characterized by their UV-Vis spectra (absorbances at 2001 wavelengths) as well as by sensorial evaluation using a nine-point scale. Four methods of discriminant analysis and artificial neural networks were used for chemometrical data processing in order to accomplish the classification of the oil. The applied approach did not depend on chemical standards, required less laboratory work but demanded more calculation efforts. The technique of K-th nearest neighbour was the best for oil classification by variety since 98.7% of the samples were correctly classified. Linear discriminant analysis was the best for oil classification by sensorial quality since 89.0% of the samples were correctly classified. The latter method was also very successful at classification by origin since 98.4% of the samples were correctly classified.

Kľúčové slová: olive oil; electronic spectra; sensorial evaluation; classification; discriminant analysis; artificial neural networks

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