Abstract
An analytical method for a rapid and nondestructive classification and authentication of whiskies of high commercial value based on trademark and years of aging is presented. Molecular absorption spectroscopy was performed with a minimum manipulation of the sample. Different conditions previous to the chemometric analysis, such as dilution and pH effect, were studied. Fifteen commercial trademarks of whiskies with different years of aging were acquired from the local market. The pattern recognition was performed using principal component analysis (PCA), linear discriminant analysis (LDA), and partial least square discriminant analysis (PLS-DA) to obtain models that allowed the classification and discrimination of whiskies based in trademarks and years of aging, respectively. Results show that by LDA, a mean of 99.15 % of samples was correctly classified according to trademark. On the other hand, by PLS-DA, a 100 % of correct classification and discrimination was achieved with several aging labels (6, 8, 12, and 15 years of aging).
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Acknowledgements
The authors wish to thank the financial support from Univ. Nacional de San Luis, Univ. Nacional de La Pampa, and Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET). Also, we want to thank Prof. Roberto Olsina (Univ. Nacional de San Luis) for providing The Unscrambler 6.11 software; and Facultad de Agronomía, Univ. Nacional de La Pampa, for providing the InfoStat software.
Conflict of Interest
Miguel Ángel Cantarelli declares that he has no conflict of interest. Silvana Mariela Azcarate declares that she has no conflict of interest. Marianela Savio declares that she has no conflict of interest. Eduardo Jorge Marchevsky declares that he has no conflict of interest. José Manuel Camiña declares that he has no conflict of interest. This article does not contain any studies with human or animal subjects.
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Cantarelli, M.Á., Azcarate, S.M., Savio, M. et al. Authentication and Discrimination of Whiskies of High Commercial Value by Pattern Recognition. Food Anal. Methods 8, 790–798 (2015). https://doi.org/10.1007/s12161-014-9958-8
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DOI: https://doi.org/10.1007/s12161-014-9958-8