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

Autor(es)

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

Afiliação do(s) autor(es)

^[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

• Tipo de documento: Artigo Científico
• Fonte: JOURNAL OF CHEMICAL TECHNOLOGY AND BIOTECHNOLOGY; v. 93, n. 4, p. 1031-1043, APR 2018.
• Citações Web of Science: 1

Resumo

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)

• Processo FAPESP: 08/57873-8 - Um processo integrado para produção total de bioetanol e emissão zero de CO2
• Beneficiário: Rubens Maciel Filho
• Modalidade de apoio: Auxílio à Pesquisa - Programa BIOEN - Temático
• Processo FAPESP: 16/01785-0 - Produção de butanol a partir de madeira de eucalipto: efeito do glicerol na desintoxicação in situ de inibidores microbianos derivados de material lignocelulósico e análise in silico do metabolismo do Clostridium beijerinckii NCIMB 8052
• Beneficiário: Elmer Alberto Ccopa Rivera
• Modalidade de apoio: Bolsas no Exterior - Pesquisa
• Processo FAPESP: 12/10857-3 - Modelagem e avaliação de diferentes cenários operacionais dos processos de pré-tratamento, hidrólise e fermentação para a produção de etanol 2g
• Beneficiário: Laura Plazas Tovar
• Modalidade de apoio: Bolsas no Brasil - Pós-Doutorado