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Quality changes and predictive models of radial basis function neural networks for brined common carp (Cyprinus
Chunli Kong1, Huiyi Wang1, Dapeng Li1
1Beijing Advanced Innovation Center for Food Nutrition and Human Health, College of Food Science and Nutritional Engineering, China Agricultural University, Beijing 100083, PR China.
Abstract:
To investigate and predict quality of 2% brined common carp (Cyprinus carpio) fillets during frozen storage, free fatty acids (FFA), salt extractable protein (SEP), total sulfhydryl (SH) content, and Ca(2+)-ATPase activity were determined at 261 K, 253 K, and 245 K, respectively. There was a dramatic increase (P<0.05) in FFA and a sharp decrease (P<0.05) in SH at 261 K during the first 3 weeks. SEP decreased to 67.31% after 17 weeks at 245 K, whereas it took about 7 weeks and 13 weeks to decrease to the same extent at 261 K and 253 K, respectively. Ca(2+)-ATPase activity kept decreasing to 18.28% after 7 weeks at 261 K. Furthermore, radial basis function neural networks (RBFNNs) were developed to predict quality (FFA, SEP, SH, and Ca(2+)-ATPase activity) of brined carp fillets during frozen storage with relative errors all within ±5%. Thus, RBFNN is a promising method to predict quality of carp fillets during storage at 245-261 K.
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