Establishment of the Arrhenius Model and the Radial Basis Function Neural Network (RBFNN) Model to Predict Quality of Thawed Shrimp (S olenocera melantho ) Stored at Different Temperatures

Modeling relationship between protein oxidation and denaturation and texture, moisture loss of bighead carp (Aristichthys Nobilis) during frozen storage

To evaluate the effects of protein oxidation and denaturation on the fish texture and moisture loss during frozen storage, we measured the changes of protein oxidation and denaturation (salt-soluble protein (SSP), total sulfhydryl (SH), disulfide (SS), carbonyl contents and Ca²⁺ -ATPase activity), texture (hardness), and moisture loss (drip loss) of bighead carp fillets stored at -12, -20 and -28°C during 16 weeks. These data were employed to develop partial least squares regression (PLSR) model, radial basis function neural network (RBFNN) model, PLSR-RBFNN (PR) model and RBFNN-PLSR (RP) model. The results showed that the RP model provided no enhancement to RBFNN model because it had the exactly same root mean square error (RMSE) and R² . PLSR model showed better performance than other models when predicting hardness. More appropriate linear or linearity-dominant hybrid model needed to be explored to establish the relationship between protein oxidation and denaturation and texture. The PR model performed better than other models in predicting drip loss with its lower RMSE and higher R² , which revealed both linear and nonlinear relationship between protein oxidation and denaturation and moisture loss. Therefore, the PR model was a promising and encouraging tool to provide a more comprehensive understanding of the relationship between protein oxidation and denaturation and moisture loss of fish during frozen storage. PRACTICAL APPLICATION: The study explored the effects of protein oxidation and denaturation on the texture and moisture loss of bighead carp during frozen storage (-12 to -28°C). PLSR model showed better performance than other models when predicting the relationship between protein oxidation and denaturation and texture. The PR model was an available tool for manufacturers to predict the relationship between protein oxidation and denaturation and moisture loss.

Frozen kinetics models for sensory, chemical, and microbial spoilage of preserved razor clam (Sinonovacula constricta) at different temperatures

Refrigerated treatment offers an effective avenue to delay spoilage process of aquatic products during storage, while none or less study has been reported for bivalve species. This work aims to investigate the variations in different storage freshness of frozen razor clam samples, by which an effective evaluation system based on frozen kinetics models was established. In this study, fresh razor clam samples were preserved at the temperature of 268, 258, and 248 K for 40 days, respectively. The spoilage process was determined by a series of freshness assays, including sensory score (SS), electric conduction (EC), total volatile basic nitrogen (TVB-N), K-value, and total colonies counts (TCC). On this basis, the variations in these indexes were fitted by zero-, first- and second- order kinetic models. Results showed that zero -order kinetic model was more suitable to fit each freshness trend. Accordingly, the shelf life of razor clam was predicted as 47∼54, 79∼84, and 121∼154 days when the samples were preserved at 268, 258, and 248 K, respectively. This study revealed the general trends of the frozen decay process of bivalve species, which is instructive to establish applicative models for the real distribution chain.