Optimization of the hydrolysis of lignocellulosic residues by using radial basis functions modeling and particle swarm optimization
dc.citation.title | Biochemical Engineering Journal | en |
dc.citation.volume | 80 | en |
dc.contributor.other | Simonetta, Arturo: for sharing his milling equipment. | |
dc.creator | Olivieri, Alejandro César | |
dc.creator | Goicoechea, Héctor Casimiro | |
dc.creator | Beccaria, Alejandro José | |
dc.creator | Giordano, Pablo César | |
dc.date.accessioned | 2018-06-12T12:51:30Z | |
dc.date.available | 2018-06-12T12:51:30Z | |
dc.date.issued | 2013-11-15 | |
dc.description | The concentrations of glucose and total reducing sugars obtained by chemical hydrolysis of three different lignocellulosic feedstocks were maximized. Two response surface methodologies were applied to model the amount of sugars produced: (1) classical quadratic least-squares fit (QLS), and (2) artificial neural networks based on radial basis functions (RBF). The results obtained by applying RBF were more reliable and better statistical parameters were obtained. Depending on the type of biomass, different results were obtained. Improvements in fit between 35% and 55% were obtained when comparing the coefficients of determination (R²) computed for both QLS and RBF methods. Coupling the obtained RBF models with particle swarm optimization to calculate the global desirability function, allowed to perform multiple response optimization. The predicted optimal conditions were confirmed by carrying out independent experiments. | es |
dc.description.fil | Fil: Giordano, Pablo César. Universidad Nacional del Litoral. Facultad de Bioquímica y Ciencias Biológicas. Cátedra de Química Analítica I. Laboratorio de Desarrollo Analítico y Quimiometría (LADAQ); Argentina. | es |
dc.description.fil | Fil: Giordano, Pablo César. Universidad Nacional del Litoral. Facultad de Bioquímica y Ciencias Biológicas. Laboratorio de Fermentaciones; Argentina. | es |
dc.description.fil | Fil: Beccaria, Alejandro José. Universidad Nacional del Litoral. Facultad de Bioquímica y Ciencias Biológicas. Laboratorio de Fermentaciones; Argentina. | es |
dc.description.fil | Fil: Goicoechea, Héctor Casimiro. Universidad Nacional del Litoral. Facultad de Bioquímica y Ciencias Biológicas. Cátedra de Química Analítica I. Laboratorio de Desarrollo Analítico y Quimiometría (LADAQ); Argentina. | es |
dc.description.fil | Fil: Olivieri, Alejandro César. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Instituto de Química de Rosario (IQUIR-CONICET); Argentina. | es |
dc.description.sponsorship | Universidad Nacional del Litoral: Project CAI+D Nº 12-65 y CAI+D 2009 Tipo III R2 | es |
dc.description.sponsorship | Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET): Project PIP 2988 | es |
dc.description.sponsorship | Agencia Nacional de Promoción Científica y Tecnológica (ANPCyT): Project PICT 2010-0084 | es |
dc.format | application/pdf | |
dc.format.extent | 1-9 | en |
dc.identifier.issn | 1369-703X | |
dc.identifier.uri | http://hdl.handle.net/2133/11441 | |
dc.language.iso | eng | es |
dc.publisher | Elsevier | es |
dc.relation.publisherversion | https://www.sciencedirect.com/science/article/pii/S1369703X13002453 | es |
dc.relation.publisherversion | http://dx.doi.org/10.1016/j.bej.2013.09.004 | es |
dc.rights | openAccess | es |
dc.rights.holder | Olivieri, Alejandro César | es |
dc.rights.holder | Goicoechea, Héctor Casimiro | es |
dc.rights.holder | Beccaria, Alejandro José | es |
dc.rights.holder | Giordano, Pablo César | es |
dc.rights.holder | Universidad Nacional de Rosario | es |
dc.rights.holder | Universidad Nacional del Litoral | es |
dc.rights.holder | Elsevier | es |
dc.rights.text | Atribución-NoComercial-SinDerivadas 4.0 Internacional (CC BY-NC-ND 4.0) | es |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-sa/2.5/ar/ | * |
dc.subject | Glucose | es |
dc.subject | Hydrolysis | es |
dc.subject | Biomass | es |
dc.subject | Lignocellulose | es |
dc.subject | Neural Networks | es |
dc.title | Optimization of the hydrolysis of lignocellulosic residues by using radial basis functions modeling and particle swarm optimization | es |
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