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Low field nuclear magnetic resonance and multivariate analysis for prediction of physicochemical characteristics of Atlantic mackerel as affected by season of catch, freezing method, and frozen storage duration. | LitMetric

AI Article Synopsis

Article Abstract

Fast and non-destructive prediction of the quality characteristics of food products during frozen storage are of great value both for the food industry and the consumers. The current study investigated the potential of using low field Nuclear Magnetic Resonance (NMR) along with multivariate chemometric methods to predict various important physicochemical quality parameters in Atlantic mackerel during frozen storage, as affected by season of catch, freezing method and temperature, as well as frozen storage duration. The obtained results clearly showed that transverse relaxation data obtained by low field NMR can be effectively used to simultaneously predict multiple quality characteristics of the mackerel fillets through storage, including water and lipid content, water holding capacity, lipid oxidation (peroxide value (PV), and thiobartituric reactive substances (TBARS)) and lipid hydrolysis (free fatty acids (FFA)) content within the muscle. The NMR data could furthermore be used to predict variations in the muscle due to season of catch, the frozen storage duration of the mackerel samples when all samples were used, and whether the fish had been headed and gutted or stored whole, which freezing equipment had been used, and the frozen storage temperature for mackerel samples caught at the end of July. Simplified monitoring and optimization of these quality parameters in frozen mackerel with a fast and non-destructive analytical technique like low field NMR is thus of great value for the fishing industry.

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Source
http://dx.doi.org/10.1016/j.foodres.2018.08.063DOI Listing

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