Optimization and modeling of cellulase protein from Trichoderma reesei Rut C30 using mixed substrate

Abstract

Bioethanol from cellulosic raw material has proved to be the best alternative renewable energy source. Cellulase is a multienzyme complex catalyses the bioconversion of cellulose to glucose, which can be
used for ethanol production. The objective of this research is to reduce the cost of cellulase production by optimization of fermentation conditions and modeling of the fermentation process. Research surface methodology was suggested for optimization of process conditions of cellulase biosynthesis.
Logistic kinetic model was the best model for the mixed substrates. A conceptual Artificial Neural Network (ANN) model was well incorporated in the fermentative production of cellulase. By adopting these models high yield of cellulase was obtained.