Modeling the Kinetics of Complex Systems: Enzymatic Hydrolysis of Lignocellulosic Substrates

Lignocellulosic biomass is mainly composed of cellulose, hemicellulose, and lignin. Fuzzy logic, in turn, is a branch of many-valued logic based on the paradigm of inference under vagueness. This paper presents a methodology, based on computational intelligence, for modeling the kinetics of a comple...

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Bibliographic Details
Published in:Applied biochemistry and biotechnology 2014-07, Vol.173 (5), p.1083-1096
Main Authors: Suarez, Carlos Alberto Galeano, Cavalcanti-Montaño, Inti Doraci, da Costa Marques, Renan Gustavo, Furlan, Felipe Fernando, da Mota e Aquino, Pedro Luiz, de Campos Giordano, Roberto, de Sousa, Ruy, Jr
Format: Article
Language:English
Subjects:
Animals
artificial intelligence
Biochemistry
Biological and medical sciences
Biomass
Bioreactors
Biotechnology
Cellulase - metabolism
Cellulose
Chemistry
Chemistry and Materials Science
Cluster Analysis
engineering
enzymatic hydrolysis
Enzyme kinetics
Experimental data
Fundamental and applied biological sciences. Psychology
fuzzy logic
hemicellulose
Hydrolysis
Kinetics
lignin
Lignin - metabolism
Lignocellulose
Membrane reactors
Models, Chemical
Trichoderma - enzymology
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Summary:Lignocellulosic biomass is mainly composed of cellulose, hemicellulose, and lignin. Fuzzy logic, in turn, is a branch of many-valued logic based on the paradigm of inference under vagueness. This paper presents a methodology, based on computational intelligence, for modeling the kinetics of a complex reactional system. The design of a fuzzy interpolator to model cellulose hydrolysis is reported, within the perspective of applying kinetic models in bioreactor engineering. Experimental data for various types of lignocellulosic materials were used to develop the interpolator. New experimental data from the enzymatic hydrolysis of a synthetic substrate, on the other hand, were used to validate the methodology. The accuracy of the results indicates that this is a promising approach to extend the application of models fitted for specific situations to different cases, thus enhancing their generality.
ISSN:0273-2289
1559-0291
DOI:10.1007/s12010-014-0912-4