Authentication of tequilas using pattern recognition and supervised classification

UDC.coleccionInvestigaciónes_ES
UDC.departamentoCiencias da Computación e Tecnoloxías da Informaciónes_ES
UDC.endPage129es_ES
UDC.grupoInvRedes de Neuronas Artificiais e Sistemas Adaptativos -Informática Médica e Diagnóstico Radiolóxico (RNASA - IMEDIR)es_ES
UDC.journalTitleTrAC Trends in Analytical Chemistryes_ES
UDC.startPage117es_ES
UDC.volume94es_ES
dc.contributor.authorPérez-Caballero, G.
dc.contributor.authorAndrade-Garda, José Manuel
dc.contributor.authorOlmos, P.
dc.contributor.authorMolina, Y.
dc.contributor.authorJiménez, I.
dc.contributor.authorDurán, J.J.
dc.contributor.authorFernández-Lozano, Carlos
dc.contributor.authorMiguel-Cruz, F.
dc.date.accessioned2019-04-26T08:58:30Z
dc.date.available2019-04-26T08:58:30Z
dc.date.issued2017-07-18
dc.description.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.es_ES
dc.description.sponsorshipXunta de Galicia; GRC2013-047es_ES
dc.description.sponsorshipMinisterio de Industria, Energía y Competitividad; FJCI-2015-26071es_ES
dc.identifier.citationPérez-Caballero G, Andrade JM, Olmos P, et al. Authentication of tequilas using pattern recognition and supervised classification. TrAC Trends Anal Chem. 2017; 94: 117-129es_ES
dc.identifier.issn0165-9936
dc.identifier.urihttp://hdl.handle.net/2183/22768
dc.language.isoenges_ES
dc.publisherElsevieres_ES
dc.relation.urihttps://doi.org/10.1016/j.trac.2017.07.008es_ES
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 Españaes_ES
dc.rights.accessRightsopen accesses_ES
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/*
dc.subjectTequilaes_ES
dc.subjectSupervised classificationes_ES
dc.subjectAuthenticationes_ES
dc.subjectDimensionality reductiones_ES
dc.subjectMachine learninges_ES
dc.titleAuthentication of tequilas using pattern recognition and supervised classificationes_ES
dc.typejournal articlees_ES
dspace.entity.typePublication
relation.isAuthorOfPublicationbe8f36be-955f-482b-a5b9-c4d407386971
relation.isAuthorOfPublicatione5ddd06a-3e7f-4bf4-9f37-5f1cf3d3430a
relation.isAuthorOfPublication.latestForDiscoverybe8f36be-955f-482b-a5b9-c4d407386971

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