Enzymatic Hydrolysis Prediction Model of Bone Collagen from Pollock Based on Intrinsic Viscosity
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    Abstract:

    Collagen was extracted from pollock bones and hydrolyzed with trypsin. An enzymatic hydrolysis prediction model of pollock bone collagen was established based on artificial neural network. It shows that the viscosity of collagen and its hydrolysates is decreased with the increasing of temperature. With the hydrolysis degree increasing, the peptide chain length, the molecular weight decrease, and the intrinsic viscosity decrease. In addition, it exhibited a one to one mapping relationship between the hydrolysis degree and the intrinsic viscosity. Using the intrinsic viscosity and the temperature as input parameters and the degree of hydrolysis as output parameter, a neural network was trained and simulated by 51 samples. The value of R2 is 0.9916 and the average relative error is only 2.5%, which indicates a good relevance between the sample actual value and the simulation value. Then three verification tests were performed using the prediction model, and the theoretical value is in agreement with the experimental value. The relative error is in range of 1.06%~4.32%. Therefore, the model can predict and monitor the hydrolysis of pollock bone collagen.

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History
  • Received:April 03,2013
  • Revised:
  • Adopted:
  • Online: March 10,2014
  • Published: February 10,2014
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