Potential of fluorescence fingerprints for fish meat authentication: Differences in freshness evaluation in white and dark meat at frozen state

Author:

Rahman Md. Mizanur123ORCID,Shibata Mario3,Nakazawa Naho3,Rithu Mst. Nazira Akhter4,Okazaki Emiko3,Nakauchi Shigeki1

Affiliation:

1. Department of Computer Science and Engineering Toyohashi University of Technology Toyohashi Aichi Japan

2. Department of Fisheries Technology Patuakhali Science and Technology University Dumki Patuakhali Bangladesh

3. Department of Food Science and Technology Tokyo University of Marine Science and Technology Minato Tokyo Japan

4. Department of Ocean Sciences Tokyo University of Marine Science and Technology Minato Tokyo Japan

Abstract

AbstractAs dark meat has a faster deterioration rate and its unintentional mixing occurs during processing, it is crucial to know the status and freshness indicators of dark meat to ensure fishery product quality. In this method, fluorescence fingerprints (FFs) was applied as a rapid and noninvasive quality authentication method to determine differences between white and dark meat in the evaluation of freshness indicators at frozen state. Spotted mackerel (Scomber australasicus) fish chunks with different postmortem conditions (0–40 h ice stored) were obtained and frozen. A new generation of fluorescence spectrophotometer (F‐7100) was used to acquire FFs of the frozen fish chunks (containing white and dark meat). Adenosine triphosphate metabolites and pH were determined in both white and dark meat using their relevant biochemical methods. Higher K‐values in dark meat might be attributed to a higher accumulation rate of inosine (HxR) in dark meat than in white meat. The pH decrease rate in white meat was higher than that in dark meat during postmortem ice storage periods of fish. Principal component analysis of FFs spectra demonstrated clear discrimination (PC1 + PC2 = 91.7%) between white and dark meat of frozen fish due to the influence of freshness parameters based on the fluorescence features of fish meat. Furthermore, partial least squares regression validation models revealed that freshness indicators of white meat could be predicted more accurately at the frozen state than those of dark meat. This method could be applied during the processing of fishery products, thereby facilitating quality control activities and making it a promising authentication tool for the fisheries industries.

Funder

Japan Society for the Promotion of Science

Publisher

Wiley

Subject

Food Science

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