Prediction of overall glucose yield in hydrolysis of pretreated sugarcane bagasse using a single artificial neural network: good insight for process development-Reference-Cited by-同舟云学术

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

Published:2017-11-23 Issue:4 Volume:93 Page:1031-1043
ISSN:0268-2575
Container-title:Journal of Chemical Technology & Biotechnology
language:en
Short-container-title:J. Chem. Technol. Biotechnol

Author:

Plazas Tovar Laura¹²^ORCID,Ccopa Rivera Elmer²³,Pinto Mariano Adriano²,Wolf Maciel Maria Regina²,Maciel Filho Rubens²

Affiliation:

1. Department of Chemical Engineering; Federal University of Santa Maria; Santa Maria-RS Brazil

2. School of Chemical Engineering; University of Campinas; Campinas-SP Brazil

3. The Ohio State University; Department of Animal Sciences; Wooster OH USA

Funder

Fundação de Amparo à Pesquisa do Estado de São Paulo

Publisher

Wiley

Subject

Inorganic Chemistry,Organic Chemistry,Pollution,Waste Management and Disposal,Fuel Technology,Renewable Energy, Sustainability and the Environment,General Chemical Engineering,Biotechnology

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4. Enhanced saccharification of cellulose and sugarcane bagasse by Clostridium thermocellum cultures with Triton X-100 and [small beta]-glucosidase/Cellic[registered sign]CTec2 supplementation;X-S;RSC Adv,2017

5. Neural network modeling to predict the total glucose yield after enzymatic saccharification of H2SO4-catalyzed hydrothermally pretreated sugarcane bagasse;Rivera;Chem Eng Trans,2015

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