SACCHAROMYCES CEREVISIAE FED-BATCH FERMENTATION AND ARTIFICIAL INTELLIGENCE METHOD FOR ADJUSTING MODEL PARAMETERS TO EXPERIMENTAL DATA

SACCHAROMYCES CEREVISIAE FED-BATCH FERMENTATION AND ARTIFICIAL INTELLIGENCE METHOD FOR ADJUSTING MODEL PARAMETERS TO EXPERIMENTAL DATA

SOARES, M. C. P.; LUZ, G. F.; COSTA, A. C.; GOMES, M. K.; MENDES, B. F.; TORRE, L. G.; FUJIWARA, E.

Pôster:

The fermentation process parameters vary with a range of factors, suchas temperature and the composition of the fermentation broth. In order for being usedas important project and process monitoring tools, these parameters should beconstantly recalculated. In this research, a fermentation model for fed-batch reactionmode is presented, and experimental data are used for showing computationmethodologies for recalculating the parameters.

The fermentation process parameters vary with a range of factors, suchas temperature and the composition of the fermentation broth. In order for being usedas important project and process monitoring tools, these parameters should beconstantly recalculated. In this research, a fermentation model for fed-batch reactionmode is presented, and experimental data are used for showing computationmethodologies for recalculating the parameters.

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DOI: 10.5151/cobeq2018-PT.0532

Referências bibliográficas

• [1] ANDRADE RR, RIVERA EC, ATALA DIP, MACIEL FILHO R, MAUGIERI FILHO F, COSTA AC. Study of kinetic parameters in a mechanistic model for bioethanol production through a screening technique and optimization. Bioprocess Biosyst. Eng., v.32, p. 673-680, 2009. ATALA DIP, COSTA AC, MACIEL FILHO R, MAUGERI FILHO F. Kinetics of ethanol fermentation with high biomass concentration considering the effect of temperature. Appl. Biochem. Biotechnol., v.91-93, p. 353-364, 2001. BAILEY J, OLLIS D. Biochemical Engineering Fundamentals. Second Edition. McGraw-Hill, 1986. DORAN P. Bioprocess Engineering Principles. Second Edition. Elsevier, 2013. FUJIWARA E, ONO E, IAMAKAWA CK, IENCZAK JL, ROSSELL CEV, SUZUKI CK. Realtime monitoring of fermentation process applied to sugarcane bioethanol production. OFS-22, Beijing, China, 2012. POWCHINDA O, STREHAIANO P. Utilization of Mixed Sugars for Alcoholic Fermentation by Saccharomyces cerevisiae. Thammasat Int. J. Sci. Tech., v.4, p. 23-31, 1999. RIVERA EC, COSTA AC, ANDRADE RR, ATALA DIP, MAUGIERI FILHO F, MACIEL FILHO R. Development of adaptive modeling techniques to describe the temperature-dependent kinetics of biotechnological processes. Biochem. Eng. J., v.36, p. 157-166, 2007. SHULER M, KARGI F. Bioprocess Engineering. Basic Concepts. Second Edition. Prentice Hall, 2002. WANG F-S, SHEU, J-W. Multiobjective parameter estimation problems of fermentation processes using a high ethanol tolerance yeast. Chem. Eng. Sci, v.55, p. 3685-3695, 2000.

Como citar:

SOARES, M. C. P. ; LUZ, G. F. ; COSTA, A. C. ; GOMES, M. K.; MENDES, B. F. ; TORRE, L. G. ; FUJIWARA, E.; "SACCHAROMYCES CEREVISIAE FED-BATCH FERMENTATION AND ARTIFICIAL INTELLIGENCE METHOD FOR ADJUSTING MODEL PARAMETERS TO EXPERIMENTAL DATA", p-2010-2014. In: . São Paulo: Blucher, 2018.
ISSN 23591757, DOI 10.5151/cobeq2018-PT.0532