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dc.contributor.authorReguera Alonso, Celia 
dc.contributor.authorSanllorente Méndez, Silvia 
dc.contributor.authorHerrero Gutiérrez, Ana 
dc.contributor.authorSarabia Peinador, Luis Antonio 
dc.contributor.authorOrtiz Fernández, Mª Cruz 
dc.date.accessioned2019-05-20T08:48:29Z
dc.date.issued2019-09
dc.identifier.issn0039-9140
dc.identifier.urihttp://hdl.handle.net/10259/5092
dc.description.abstractThe maintenance of the cold chain is essential to ensure foodstuff conformity and safety. However, gaps in the cold chain may be expected so designing analytical methods capable to detect cold chain breaks is a worthwhile issue. In this paper, the possibility of using the amount of nine biogenic amines (BAs) determined in Thunnus albacares by HPLC-FLD for detecting cold chain breaks is approached. Tuna is stored at 3 different temperature conditions for 8 storage periods. The evolution of the content of BAs is analyzed through parallel factor analysis (PARAFAC), in such a way that storage temperature, BAs and storage time profiles are estimated. PARAFAC has made it possible to observe two spoilage routes with different relative evolution of BAs. In addition, it has enabled to estimate the storage time, by considering the three storage temperatures, with errors of 0.5 and 1.0 days in fitting and in prediction, respectively. Furthermore, a class-modelling technique based on partial least squares is sequentially applied to decide, from the amount of BAs, if there has been a cold chain break. Firstly, samples stored at 25 °C are statistically discriminated from those kept at 4 °C and −18 °C; next, frozen samples are distinguished from those refrigerated. In the first case, the probabilities of false non-compliance and false compliance are almost zero, whereas in the second one, both probabilities are 10%. Globally, the results of this work have pointed out the feasibility of using the amount of BAs together with PLS-CM to decide if the cold chain has been maintained or not.en
dc.description.sponsorshipAgencia Estatal de Investigación of Spanish Ministerio de Economía, Industria y Competitividad, Gobierno de España [project CTQ2017-88894-R] and Consejería de Educación de la Junta de Castilla y León [project BU012P17] both co-financed with European Regional Development Funden
dc.format.mimetypeapplication/pdf
dc.language.isoenges
dc.publisherElsevieren
dc.relation.ispartofTalanta. 2019, V. 202, p. 443-451en
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectBiogenic aminesen
dc.subjectCold chainen
dc.subjectPartial least squares - class modellingen
dc.subjectHPLC-FLDen
dc.subjectParallel factor analysisen
dc.subjectSpoilage of tunaen
dc.subject.otherQuímica analíticaes
dc.subject.otherChemistry, Analyticen
dc.titleDetection of cold chain breaks using partial least squares-class modelling based on biogenic amine profiles in tunaen
dc.typeinfo:eu-repo/semantics/article
dc.date.embargo2021-09-01
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess
dc.relation.publisherversionhttps://doi.org/10.1016/j.talanta.2019.04.072
dc.identifier.doi10.1016/j.talanta.2019.04.072
dc.relation.projectIDinfo:eu-repo/grantAgreement/MINECO/CTQ2017-88894-R
dc.relation.projectIDinfo:eu-repo/grantAgreement/JCyL/BU012P17
dc.type.hasVersioninfo:eu-repo/semantics/acceptedVersion


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