Prediction Model For Hydrolysis Of Cod Bone Collagen Based On Characteristic Viscosity
Keywords
Collagen, Enzymatic Hydrolysis Products, Characteristic Viscosity, Neural Network, Prediction Model
Abstract
Collagen was prepared from cod bone and enzymatically hydrolyzed. An artificial neural network was used to establish a prediction model for the enzymatic hydrolysis reaction of cod bone collagen. The results show that the viscosity of collagen and hydrolysates decreases with the increase of temperature. As the degree of hydrolysis of collagen deepens, the length and molecular weight of the peptide chain decrease, and the characteristic viscosity shows a downward trend. The degree of hydrolysis and the characteristic viscosity are mapped one by one. relation. Using the characteristic viscosity and temperature of the hydrolyzate as input parameters and the degree of hydrolysis as the output parameter, a neural network prediction model was established. The R2 value between the sample value and the simulation value is 0.9916, and the average relative error is 2.5%. The built network prediction model has good performance and high prediction accuracy. The relative error of the verification test is 1.06% to 4.32%, realizing the simulation prediction and monitoring of the cod bone collagen proteolysis reaction.
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Original research was done by Hou Hu, Peng Zhe, Su Shiwei, Lu Jiaohan, Li Bafang
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