Sugarcane molasses fermentation with in situ gas stripping using low and moderate sugar concentrations for ethanol production: Experimental data and modeling

•Modeling of gas stripping fermentation was performed.•Ethanol concentration was maintained below threshold of toxicity.•An increase in yield and productivity of ethanol was observed.•A model which combines kinetics and thermodynamics was proposed.•Genetic algorithm methodology was used to estimate...

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Bibliographic Details
Published in:Biochemical engineering journal 2016-06, Vol.110, p.152-161
Main Authors: Ponce, Gustavo Henrique Santos F., Moreira Neto, João, De Jesus, Sérgio Santos, Miranda, Júlio César de Carvalho, Maciel Filho, Rubens, Andrade, Rafael Ramos de, Wolf Maciel, Maria Regina
Format: Article
Language:English
Subjects:
Ethanol
Fermentation
Gas-liquid mass transfer
Modelling
Product inhibition
Saccharomyces cerevisiae
Sugarcane molasses
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Summary:•Modeling of gas stripping fermentation was performed.•Ethanol concentration was maintained below threshold of toxicity.•An increase in yield and productivity of ethanol was observed.•A model which combines kinetics and thermodynamics was proposed.•Genetic algorithm methodology was used to estimate the kinetic parameters. In this study, the feasibility of gas stripping technique was studied for Brazilian sugarcane industry conditions: Saccharomyces cerevisiae yeast and sugarcane molasses as raw material. The experimental trials were carried out in batch into two levels of gas flow rate (4 and 6L/min) and sugar concentration (170 and 250g/L). Results showed that the gas stripping technique was effective since ethanol concentration was maintained below threshold of toxicity (no more than 60g/L in all cases), as well as sugar containing was consumed almost completely. Furthermore, a mixed mathematical model combining a complex term for the ethanol entrainment from gas stripping fermentation was proposed based in robust models for sugarcane molasses previously presented in literature. ParametersYpx, μmax, Pmax, Yx, Xmax were estimated and presented itself within previous ranges validated for sugarcane molasses. The methodology of parameters estimation using genetic algorithms showed to have good performance, and the model was able to predict the data set of glucose, biomass and ethanol concentrations in low and high levels of sugarcane molasses in the broth, with only one set of parameters.
ISSN:1369-703X
1873-295X
DOI:10.1016/j.bej.2016.02.007