Freshness estimation models of dressed puffers (Migaki) based on fish body surface colors
2019
Nakamura, M. (National Fisheries University, Fisheries Research and Education Agency, Shimonoseki, Yamaguchi (Japan)) | Shiigi, T. | Watanabe, T. | Tokunaga, K. | Takaoka, Y. | Maeda, T.
Models which ensure accurate non-destructive estimates of the freshness of fish meat (K value) in real time are proposed to improve quality control and maintain the skill level of distributers of dressed puffers (Migaki). Seven kinds of dressed puffers were used to construct the models for estimating fish meat freshness. Relationships between fish coloration and K values from sample acquisition until 72 hours later under refrigeration at -2℃, +2℃, and +6℃ were investigated. The statistical analysis revealed that fish coloration does reflect its K value, although the strength of the relationship differs according to fish species. Two models were designed on the basis of these results, and the usefulness of each model was evaluated. The models are as follows: (1) Model to infer the K value of fish meat based on the coloration of the fish body surface by using fuzzy inference (Model 1), and (2) Model to estimate the K value of fish meat after several hours for the same fish for which the K value was inferred with Model 1 (Model 2). For these models, a high estimation accuracy was confirmed, demonstrating their potential usefulness for quality control in the distribution of dressed puffers.
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