Modelling of the kinetics of red tilapia (Oreochromis spp.) viscera enzymatic hydrolysis using mathematical and neural network models

Abstract

ABSTRACT: The present work modelled the enzymatic hydrolysis of red tilapia (Oreochromis spp.) viscera with Alcalase® 2.4 L in both 0.5 and 5 L reactors. The best conditions for the enzymatic hydrolysis were 60°C and pH 10. The product inhibited the enzymatic hydrolysis, and the enzyme deactivated following second-order reaction. KM and Kp from a secondary plot of KM app as a function of inhibitor concentration, and k2, p, and k3 were found by non-linear regression. While the obtained parameters modelled the 0.5 L reactor well, it did not model the 5 L reactor, probably because of unconsidered fluid dynamics in the model. To have a better modelling, a neural network (tensorflow.keras.models module) was built and trained. The neural network modelled the enzymatic hydrolysis of red tilapia at several concentrations of substrate and enzyme. This result proved that neural networks are a powerful tool for modelling biological processes.