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dc.contributor.authorAres Sacristán, Ana María 
dc.contributor.authorRedondo, Montserrat
dc.contributor.authorTapia García, Jesús Alberto 
dc.contributor.authorGonzález-Porto, Amelia V.
dc.contributor.authorHiges, Mariano
dc.contributor.authorMartín-Hernández, Raquel
dc.contributor.authorBernal del Nozal, José 
dc.date.accessioned2024-01-10T17:59:45Z
dc.date.available2024-01-10T17:59:45Z
dc.date.issued2020
dc.identifier.citationLWT - Food Science and Technology, Mayo 2020, vol. 2020, n. 109559.es
dc.identifier.urihttps://uvadoc.uva.es/handle/10324/64404
dc.descriptionProducción Científicaes
dc.description.abstractA study is presented of the real possibilities of glucosinolate content and chemometrics (canonical discriminant analysis) to differentiate bee pollen samples from four different apiaries (Fuentelahiguera, Monte, Pistacho, Tío Natalio) located in the same geographical area. Fifteen intact-glucosinolates were quantified by means of ultraperformance liquid chromatography coupled to a quadrupole time-of-flight mass detector in forty-nine bee pollen samples. Glucosinolate residues were detected in most of the samples, and these differed in number and concentration. It was possible to directly differentiate one of the apiaries (Fuentelahiguera) from the other three (Monte, Pistacho y Tío Natalio) by comparing glucosinolate content. These three apiaries were differentiated by means of the first two canonical variables obtained from a canonical discriminant analysis. Following this analysis, more than 88% of the samples could be assigned correctly to the Pistacho and Monte apiaries, and 100% to the Tío Natalio apiary.es
dc.format.mimetypeapplication/pdfes
dc.language.isoenges
dc.publisherElsevieres
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subject.classificationAuthenticity; Bee pollen; Canonical discriminant analysis; Glucosinolates; UPLC-Q-TOF/MSes
dc.titleDifferentiation of bee pollen samples according to their intact-glucosinolate content using canonical discriminant analysises
dc.typeinfo:eu-repo/semantics/articlees
dc.rights.holderElsevieres
dc.identifier.doihttps://doi.org/10.1016/j.lwt.2020.109559es
dc.relation.publisherversionhttps://www.sciencedirect.com/science/article/pii/S002364382030548X?via%3Dihubes
dc.identifier.publicationtitleLWT - Food Science and Technologyes
dc.peerreviewedSIes
dc.description.projectEste trabajo forma parte de los proyectos de investigación financiados por el Ministerio de Economía y Competitividad e INIA-FEDER (RTA2015-00013-C03-01 y 03).es
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.type.hasVersioninfo:eu-repo/semantics/acceptedVersiones


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