FOOD SCIENCE ›› 2009, Vol. 30 ›› Issue (22 ): 54-57.doi: 10.7506/spkx1002-6300-200922008

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Artificial Neural Network-based Optimization of Enzymolysis of Paphia undulate Meat for Production of Small Peptides

CHEN Xin1,2,3,SUN Hui-li2,3,HUANG Han-wen1,MIAO Qing4   

  1. (1. Department of Chemistry and Chemical Engineering, Foshan University, Foshan 528000, China;2. South China Sea Institute of
    Oceanlogy, Chinese Academy of Sciences, Guangzhou 510301, China;3. Graduate University of Chinese Academy of Sciences,
    Beijing 100049, China;4. Department of Maths, Foshan University, Foshan 528000, China)
  • Received:2008-09-19 Online:2009-11-15 Published:2010-12-29
  • Contact: CHEN Xin1,2,3, E-mail:fschenxin@tom.com

Abstract:

Based on the training of artificial neural networks (ANNs) using orthogonal arrays, a model for the productivity of small peptides as the output of the input consisting of five technological parameters for papain hydrolysis of Paphia undulate meat developed and validated for reliability using arbitrarily selected specimens. The further optimization of optimal values of these parameters obtained using orthogonal array design was conducted based on the AAN model by means of small-step search. AAN-based optimization gave a productivity of small peptides of 4.944%, higher than the value of 4.670% from orthogonal array optimization. In conclusion, our results reveal that more optimized technological parameters and higher optimization efficiency can be obtained using combined ANNs and orthogonal array design than using orthogonal array design alone.

Key words: artificial neural networks, preparation, Paphia undulate, small peptides

CLC Number: