Impact of time and temperature of storage on the spoilage of swordfish and the evolution of biogenic amines through a multiway model. (9th November 2017)

• Record Type: Journal Article
• Authors: Ortiz, M.C.; Sanllorente, S.; Herrero, A.; Reguera, C.; Sarabia, L.A.
• Is Part Of: Journal of chemometrics. Volume 32:Number 3(2018)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2017-11-09
• Subjects: biogenic amines -- false discovery rate -- HPLC‐FLD -- parallel factor analysis -- spoilage of fish -- 3‐way data; Chemistry -- Mathematics -- Periodicals; Chemistry -- Statistical methods -- Periodicals; 542.85
• DOI: 10.1002/cem.2965
• Languages: English
• ISSNs: 0886-9383

Abstract

Abstract: A new multiway/multivariate approach is proposed to study and model the spoilage of swordfish with time and temperature of storage through the profiles of putrescine, spermidine, histamine, tyramine, tryptamine, cadaverine, spermine, and 2‐phenylethylamine. The evolution of these biogenic amines in food is a complex process that cannot be characterized by a single parameter but by a modification of the amine profiles. An experimental strategy is designed to determine these profiles in such a way that data are structurally 3‐way. Modeling the joint evolution of the biogenic amines with a PARAFAC model which explains 97.8% of variability (CORCONDIA index equals 100%) leads to estimate the storage time, storage temperature, and biogenic amines profiles. A multiple regression (determination coefficient of 0.98) based on the loadings of the 2 factors of the time profile of the PARAFAC model enables the estimation of the storage time with an error of 0.5 days. Abstract : In this work, a new multiway/multivariate approach is developed to study and model the degree of spoilage of swordfish ( Xiphias gladius ) with the time and temperature of storage through the amount profiles of 8 biogenic amines (BAs). The analysis of the underlying profiles enables linking the 2 factors obtained from a PARAFAC model for each storage temperature to their specific BAs amount and storage time profiles, describing the latent structure of the evolution of BAs in the spoilage of the fish. In addition, a regression model enables the prediction of the storage time with a mean error of 0.5 days.