alexa Kinetic Modeling and Optimization of a Batch Ethanol Fermentation Process
ISSN: 2155-9821

Journal of Bioprocessing & Biotechniques
Open Access

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Research Article

Kinetic Modeling and Optimization of a Batch Ethanol Fermentation Process

Samuel C Oliveira1*, Romulo C Oliveira2, Mariana V Tacin2and Edwil AL Gattás2
1Departamento de Bioprocessos e Biotecnologia, Faculdade de Ciências Farmacêuticas, UNESP-Univ Estadual Paulista, Rodovia Araraquara-Jaú km 1, Caixa Postal 502, CEP 14801-902, Araraquara-SP, Brazil
2Departamento de Alimentos e Nutrição, Faculdade de Ciências Farmacêuticas, UNESP-Univ Estadual Paulista, Rodovia Araraquara-Jaú km 1, Caixa Postal 502, CEP 14801-902, Araraquara-SP, Brazil
Corresponding Author : Samuel C Oliveira
Departamento de Bioprocessos e Biotecnologia, Faculdade de Ciências Farmacêuticas
UNESP-Univ Estadual Paulista, Rodovia Araraquara-Jaú km 1
Caixa Postal 502, CEP 14801-902, Araraquara-SP, Brazil
Tel: +551633014646
E-mail: [email protected]
Received: January 12, 2016; Accepted: January 18, 2016; Published: January 22, 2016
Citation: Oliveira SC, Oliveira RC, Tacin MV, Gattás EAL (2016) Kinetic Modeling and Optimization of a Batch Ethanol Fermentation Process. J Bioprocess Biotech 6:266. doi:10.4172/2155-9821.1000266
Copyright: © 2016 Oliveira SC, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
 

Abstract

A simple mathematical model, taking into account substrate limitation and inhibition by both the product ethanol and the substrate, was proposed and used to interpret experimental data from a batch alcohol fermentation process, conducted at two different sets of initial concentrations of sugar and cells. A detailed sequence of mathematical model derivation and parameter estimation is presented. The temporal profiles of sugar, cell and ethanol concentrations in the culture medium were modeled by a set of ordinary differential equations, which were integrated numerically by the 4th-order Runge-Kutta-Gill method. The model was validated by real laboratory fermentations and the accuracy of the model is acceptable. The agreement between the simulation and experimental results demonstrates that the model is sufficiently reliable for prediction of the dynamic behavior of the bioprocess. A study of process optimization by means of an approximate model, used to describe the dynamics of sugar consumption, revealed the need to employ a multi-objective approach, to maximize simultaneously the ethanol productivity, ethanol concentration and the conversion of sugars.

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