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. 2024 Dec 11;13(24):4005.
doi: 10.3390/foods13244005.

Quality Differences in Frozen Mackerel According to Thawing Method: Potential Classification via Hyperspectral Imaging

Seul-Ki Park  1 , Jeong-Seok Cho  1   2 , Dong-Hoon Won  2 , Sang Seop Kim  2 , Jeong-Ho Lim  1   2 , Jeong Hee Choi  1   2 , Dae-Yong Yun  2 , Kee-Jai Park  1   2 , Gyuseok Lee  1
Affiliations

Quality Differences in Frozen Mackerel According to Thawing Method: Potential Classification via Hyperspectral Imaging

Seul-Ki Park et al. Foods. .

Abstract

Seafood quality preservation remains a critical focus in the food industry, particularly as the freeze-thaw process significantly impacts the freshness and safety of aquatic products. This study investigated quality changes in frozen mackerel subjected to two thawing methods, room temperature (RT) and running water (WT), and assessed the potential of hyperspectral imaging (HSI) for classifying these methods. After thawing, mackerel samples were stored at 5 °C for 21 days, with physicochemical, textural, and spectroscopic analyses tracking quality changes and supporting the development of a spectroscopic classification model. Compared with the WT method, the RT method delayed changes in key quality indicators, including pH, total volatile basic nitrogen (TVB-N), and total viable count (TVC), by 1-2 days, suggesting it may better preserve initial quality. Texture profile analysis showed similar trends, supporting the benefit of RT in maintaining quality. A major focus was on using HSI to assess quality and classify thawing methods. HSI achieved high classification accuracy (Rc2 = 0.9547) in distinguishing thawing methods up to three days post-thaw, with 1100, 1200, and 1400 nm wavelengths identified as key spectral markers. The HIS's ability to detect differences between thawing methods, even when conventional analyses showed minimal variation, highlights its potential as a powerful tool for quality assessment and process control in the seafood industry, enabling detection of subtle quality changes that traditional methods may miss.

Keywords: food quality; frozen mackerel; hyperspectral imaging (HSI); seafood storage; spectroscopic analysis; thawing methods.

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Conflict of interest statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Figure 1
Figure 1
Physical state and color changes in whole (A) and sliced (B) mackerel samples during storage according to the thawing method used.
Figure 2
Figure 2
Average spectra of mackerel samples by thawing method obtained using hyperspectral imaging. (A) Room-temperature thawing (RT) over the full storage duration; (B) water thawing (WT) over the full storage duration; (C) RT grouped into 4 freshness levels; (D) WT grouped into 4 freshness levels.
Figure 3
Figure 3
Beta coefficients of the PLS-DA model developed using raw hyperspectral data.
See this image and copyright information in PMC

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