Modeling of the Alcalase hydrolysis of oyster proteins using an artificial neural network

The oyster protein isolated as substrate was hydrolyzed using alkaline protease in this paper. And the experimentally determined values for the degree of hydrolysis ( DH) were used with an artificial neural network ( ANN) model to predict the Alcalase hydrolysis of the oyster protein isolated.The results showed:the coefficient of determination R2value of artificial neural network model reached 0.9998 after training. Very strong correlations were found between the calculated DH% values obtained from the ANN and those experimentally determined at the temperature, the correlation coefficient R value reached 0.9957. And in a certain range of substrate and enzyme concentration, using the ANN forecast datas, the coefficient of determination R2value of the regression equation obtained reciprocal plot reached 0.9740, the calculated kinetic constants Km and Vmax were 26.1g /L and 8.6g / ( L·min) , respectively.The results provided a reference for the artificial neural network model application in the food protease kinetic.