Pérez-Caballero, G.Andrade-Garda, José ManuelOlmos, P.Molina, Y.Jiménez, I.Durán, J.J.Fernández-Lozano, CarlosMiguel-Cruz, F.2019-04-262019-04-262017-07-18Pérez-Caballero G, Andrade JM, Olmos P, et al. Authentication of tequilas using pattern recognition and supervised classification. TrAC Trends Anal Chem. 2017; 94: 117-1290165-9936http://hdl.handle.net/2183/22768[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.engAtribución-NoComercial-SinDerivadas 3.0 Españahttp://creativecommons.org/licenses/by-nc-nd/3.0/es/TequilaSupervised classificationAuthenticationDimensionality reductionMachine learningjournal articleopen access