Discrimination between ethanol inhibition models in the continuous alcoholic fermentation process using flocculating yeast

Discrimination between different rival models for describing the inhibitory effect of ethanol both on yeast growth and on fermentation was studied for a continuous process of alcoholic fermentation in a tower reactor with recycling of flocculating cells. Models tested include linear, parabolic, hype...

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Bibliographic Details
Published in:Applied biochemistry and biotechnology 1998-09, Vol.74 (3), p.161-172
Main Authors: Oliveira, S.C. (Faculdade de Engenharia Quimica de Lorena, Lorena, Brazil.), Paiva, T.C.B, Visconti, A.E.S, Giudici, R
Format: Article
Language:English
Subjects:
Bacteriology
Biological and medical sciences
Biotechnology
Cell culture
Dilution
ETANOL
ETHANOL
Ethanol - pharmacology
ETHANOL PRODUCTION
FERMENTACION
FERMENTATION
Fermentation - drug effects
Flocculation
Fundamental and applied biological sciences. Psychology
General aspects
INHIBICION
INHIBITION
Kinetics
LEVADURA
LEVURE
Linear Models
MATHEMATICAL MODELS
Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects)
Methods. Procedures. Technologies
Microbial engineering. Fermentation and microbial culture technology
MODELE MATHEMATIQUE
MODELOS MATEMATICOS
Models, Statistical
Nonlinear Dynamics
Parameter estimation
Parameter identification
Power law
Process variables
PRODUCT INHIBITION
Saccharomyces cerevisiae - drug effects
Saccharomyces cerevisiae - metabolism
Studies
Yeast
YEASTS
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Summary:Discrimination between different rival models for describing the inhibitory effect of ethanol both on yeast growth and on fermentation was studied for a continuous process of alcoholic fermentation in a tower reactor with recycling of flocculating cells. Models tested include linear, parabolic, hyperbolic, exponential, and generalized nonlinear power-law types. The best expressions were identified under the criteria that all the kinetic parameters should assume acceptable values in a feasible range and should result in the best fit of the experimental data. The kinetic parameters were estimated from steady-state data of several sugar concentrations in feeding stream (S(0) = 160, 170, 180, 190, 200 g/L), constant dilution rate (D = 0.2 h(-1)), recycle ratio (alpha = 13.6), and temperature (T = 30 degrees C). The best model for the yeast growth was of power-law type, whereas for the product formation the best model was of linear type. These models were able to reproduce the trends of the process variables satisfactorily
ISSN:0273-2289
1559-0291
DOI:10.1007/BF02825963