Prediction of overall glucose yield in hydrolysis of pretreated sugarcane bagasse using a single artificial neural network: good insight for process development

Author(s)

Tovar, Laura Plazas ^{[1, 2]} ; Rivera, Elmer Ccopa ^{[2, 3]} ; Mariano, Adriano Pinto ^[2] ; Wolf Maciel, Maria Regina ^[2] ; Maciel Filho, Rubens ^[2]

Affiliation

^[1] Univ Fed Santa Maria, Dept Chem Engn, BR-97105900 Santa Maria, RS - Brazil

^[2] Univ Estadual Campinas, Sch Chem Engn, Campinas, SP - Brazil

^[3] Ohio State Univ, Dept Anim Sci, Wooster, OH - USA

• Document type: Journal article
• Source: JOURNAL OF CHEMICAL TECHNOLOGY AND BIOTECHNOLOGY; v. 93, n. 4, p. 1031-1043, APR 2018.
• Web of Science Citations: 1

Abstract

BACKGROUND: In this work a single artificial neural network (ANN) was used to model the overall yield of glucose (Y-GLC) as a function of a wide range of operating conditions of both pretreatment and enzymatic hydrolysis. RESULTS: The model was validated experimentally and presented good predictions of Y-GLC. Sensitivity analysis using the ANN model indicated that most of the operating parameters, except for pretreatment time, were statistically significant (P-value<0.05). Experiments showed that the processing of sugarcane bagasse (in natura) results in a satisfactory glucose yield of 69.34% when pretreated for 60 min with low initial biomass concentration and acid concentration (10% and 1.0% w/v), and followed by enzymatic hydrolysis for 72 h with 3.0% w/v substrate loading and 60 FPU per g(WIS) enzyme concentration. CONCLUSION: This study demonstrated how pretreatment and enzymatic hydrolysis data can be used to parameterize a single ANN model. Acceptable predictions of Y-GLC are achieved in terms of RSD, MSE and R-2. Supported by the model, this study provided a good insight for process development. (C) 2017 Society of Chemical Industry. (AU)

• FAPESP's process: 08/57873-8 - An integrated process for total bioethanol production and zero CO2 emission
• Grantee: Rubens Maciel Filho
• Support Opportunities: Program for Research on Bioenergy (BIOEN) - Thematic Grants
• FAPESP's process: 16/01785-0 - Butanol production from eucalyptus wood: effect of glycerol on in situ detoxification of lignocellulose-derived microbial inhibitors and in silico analysis of the metabolism of Clostridium beijerinckii NCIMB 8052
• Grantee: Elmer Alberto Ccopa Rivera
• Support Opportunities: Scholarships abroad - Research
• FAPESP's process: 12/10857-3 - MODELING AND EVALUATION OF DIFFERENT OPERATING PROCESS FOR PRE-TREATMENT, HYDROLYSIS AND FERMENTATION FOR 2G ETHANOL PRODUCTION
• Grantee: Laura Plazas Tovar
• Support Opportunities: Scholarships in Brazil - Post-Doctoral