title: Experimental study and neural network modeling of sugarcane bagasse pretreatment with H2SO4 and O3 for cellulosic material conversion to sugar.
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.
authors.affiliation: School of Chemical and Petroleum Engineering, Shiraz University, Molasadra Ave., Shiraz, Iran.
authors.forename: Vahid
authors.initials: V
authors.lastname: Gitifar
authors.forename: Reza
authors.initials: R
authors.lastname: Eslamloueyan
authors.forename: Mohammad
authors.initials: M
authors.lastname: Sarshar
mesh_terms: D050260:Carbohydrate Metabolism / Q000187:drug effects*; D002482:Cellulose / Q000737:chemistry / Q000378:metabolism*; D005947:Glucose / Q000378:metabolism; D016571:Neural Networks, Computer; D010126:Ozone / Q000494:pharmacology*; D015203:Reproducibility of Results; D031786:Saccharum / Q000737:chemistry* / Q000187:drug effects; D013464:Sulfuric Acids / Q000494:pharmacology*; D013997:Time Factors
chemical_list: D013464:Sulfuric Acids; D010126:Ozone; D002482:Cellulose; C027433:bagasse; D005947:Glucose; C033158:sulfuric acid
keywords: Optimal artificial neural networks; Ozonolysis; Pretreatment; Sugarcane bagasse; Sulfuric acid