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Título : Detection of cold chain breaks using partial least squares-class modelling based on biogenic amine profiles in tuna
Autor : Reguera Alonso, Celia
Sanllorente Méndez, Silvia
Herrero Gutiérrez, Ana
Sarabia Peinador, Luis Antonio
Ortiz Fernández, Mª Cruz
Publicado en: Talanta. 2019, V. 202, p. 443-451
Editorial : Elsevier
Fecha de publicación : sep-2019
Fecha de disponibilidad: 1-sep-2021
ISSN : 0039-9140
DOI: 10.1016/j.talanta.2019.04.072
Resumen : 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.
Palabras clave: Biogenic amines
Cold chain
Partial least squares - class modelling
Parallel factor analysis
Spoilage of tuna
Materia: Química analítica
Chemistry, Analytic
Licencia: https://creativecommons.org/licenses/by-nc-nd/4.0/
URI : http://hdl.handle.net/10259/5092
Versión del editor: https://doi.org/10.1016/j.talanta.2019.04.072
Aparece en las colecciones: Artículos Q&C

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