Abstract

ABSTRACTTo study and predict quality changes of Pacific white shrimp (Litopenaeus vannamei) during storage at different temperatures (273, 276, 279, 282, and 285 K), changes in quality of sensory assessment (SA), total aerobic counts (TAC), total volatile basic nitrogen (TVB-N), and K-value were determined. An Arrhenius model and a radial basis function neural network (RBFNN) model were built to predict quality changes of Pacific white shrimp, and the relative performances between the two models were compared. For the Arrhenius model, SA and K-values showed good performance in first-order reactions, while TAC and TVB-N showed good performance in zero-order reactions. The relative errors of the RBFNN model for all indicators were within 10%, but the range of relative errors based on the indicators of SA, TAC, TVB-N, and K-value were 1.68–81.20%, 5.54–25.50%, 2.58–71.06%, and 3.66–48.39%, respectively, for the Arrhenius model. Thus, the RBFNN model was more effective for predicting quality changes of Pacific white shrimp during storage between 273 and 285 K.

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