2026-06-20T14:22:50Zhttps://riubu.ubu.es/oai/request

oai:riubu.ubu.es:10259/50922021-11-10T09:38:26Zcom_10259_4249com_10259_5086com_10259_2604col_10259_4250

Reguera Alonso, Celia Sanllorente Méndez, Silvia Herrero Gutiérrez, Ana Sarabia Peinador, Luis Antonio Ortiz Fernández, Mª Cruz 2019-05-20T08:48:29Z 2019-09 2021-09-01 0039-9140 http://hdl.handle.net/10259/5092 10.1016/j.talanta.2019.04.072 The 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. Agencia 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 Fund application/pdf eng Elsevier Talanta. 2019, V. 202, p. 443-451 https://doi.org/10.1016/j.talanta.2019.04.072 info:eu-repo/grantAgreement/MINECO/CTQ2017-88894-R info:eu-repo/grantAgreement/JCyL/BU012P17 Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/ info:eu-repo/semantics/openAccess Biogenic amines Cold chain Partial least squares - class modelling HPLC-FLD Parallel factor analysis Spoilage of tuna Química analítica Chemistry, Analytic Detection of cold chain breaks using partial least squares-class modelling based on biogenic amine profiles in tuna info:eu-repo/semantics/article info:eu-repo/semantics/acceptedVersion