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• W4367316145 abstract "Mathematical modeling of a fermentation process is crucial in understanding and predicting dynamics of the process, which can be used in process improvement, design and control. The present study aimed to develop Monod-based kinetic models to describe cell growth, substrate consumption and ethanol production by Saccharomyces cerevisiae NP 01 under high gravity (HG) fermentation of sweet sorghum juice (SSJ). The fermentation using an initial total sugar (TS) concentration of 240 g/L resulted in 113.3 g/L of ethanol production, with 90.9% TS consumption and a fermentation efficiency of 94.4%. Growth of the yeast in terms of specific growth rate was found to be inhibited at a threshold TS concentration of 65 g/L, and the maximum specific growth rate, Monod constant and inhibition constant were 0.45 1/h, 19.5 g/L and 0.002 L/(g·h), respectively. Monod-based models incorporating substrate and product inhibition terms showed high applicability to describe the changes of cell, TS and ethanol concentrations, based on the values of bias factor, accuracy factor, coefficient of determination and root mean square error. The Monod-based models fitted the data equally well as compared with the logistic, modified Gompertz, and Weibull models, despite estimating the value of different kinetic parameters. These results demonstrated that all the models tested were applicable in modeling HG ethanol fermentation. How to cite: Salakkam A, Phukoetphim N, Laopaiboon P, et al. Mathematical modeling of bioethanol production from sweet sorghum juice under high gravity fermentation: Applicability of Monod-based, logistic, modified Gompertz and Weibull models. Electron J Biotechnol 2023;64. https://doi.org/10.1016/j.ejbt.2023.03.004." @default.
• W4367316145 created "2023-04-29" @default.
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• W4367316145 date "2023-07-01" @default.
• W4367316145 modified "2023-10-01" @default.
• W4367316145 title "Mathematical modeling of bioethanol production from sweet sorghum juice under high gravity fermentation: Applicability of Monod-based, logistic, modified Gompertz and Weibull models" @default.
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• W4367316145 doi "https://doi.org/10.1016/j.ejbt.2023.03.004" @default.
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