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Updated: May 7, 2026

High-throughput Saccharification Assay for Lignocellulosic Materials
Published on: July 3, 2011
Experimental study and neural network modeling of sugarcane bagasse pretreatment with H2SO4 and O3 for cellulosic
Vahid Gitifar1, Reza Eslamloueyan, Mohammad Sarshar
1School of Chemical and Petroleum Engineering, Shiraz University, Molasadra Ave., Shiraz, Iran.
Abstract:
In this study, pretreatment of sugarcane bagasse and subsequent enzymatic hydrolysis is investigated using two categories of pretreatment methods: dilute acid (DA) pretreatment and combined DA-ozonolysis (DAO) method. Both methods are accomplished at different solid ratios, sulfuric acid concentrations, autoclave residence times, bagasse moisture content, and ozonolysis time. The results show that the DAO pretreatment can significantly increase the production of glucose compared to DA method. Applying k-fold cross validation method, two optimal artificial neural networks (ANNs) are trained for estimations of glucose concentrations for DA and DAO pretreatment methods. Comparing the modeling results with experimental data indicates that the proposed ANNs have good estimation abilities.

