Authentication of tequilas using pattern recognition and supervised classification
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Authentication of tequilas using pattern recognition and supervised classificationAuthor(s)
Date
2017-07-18Citation
Pérez-Caballero G, Andrade JM, Olmos P, et al. Authentication of tequilas using pattern recognition and supervised classification. TrAC Trends Anal Chem. 2017; 94: 117-129
Abstract
[Abstract] Sales of reputed, Mexican tequila grown substantially in last years and, therefore, counterfeiting is increasing steadily. Hence, methodologies intended to characterize and authenticate commercial beverages are a real need. They require a combination of analytical characterization and chemometric tools. This work reports concisely on the former and focus on the chemometric tools employed so far in connection with them. Further, a practical case study presents the classification capabilities of nine supervised classification methods to differentiate white, rested, aged and extra-aged tequilas. The largest set of certified tequilas employed so far was considered. In general, non linear methods performed best than linear ones (accuracy higher than 94% in both training and validation). The case study demonstrates that it is possible to develop fast, cheap, easy to implement and reliable analytical methodologies to authenticate and classify samples of tequilas.
Keywords
Tequila
Supervised classification
Authentication
Dimensionality reduction
Machine learning
Supervised classification
Authentication
Dimensionality reduction
Machine learning
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Rights
Atribución-NoComercial-SinDerivadas 3.0 España
ISSN
0165-9936