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Modeling of ethanol fermentation from carob extract–based medium by using Saccharomyces cerevisiae in the immobilized-cell stirred tank bioreactor

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Abstract

In this study, various mathematical functions were utilized to fit the observed values and the kinetic parameters of fermentation in immobilized-cell stirred tank reactor (ICSTR) with carob extract medium (CEM). The best model was selected based on the residual sum of squares (RSS), root-mean-square-error (RMSE), mean-absolute-error (MAE), determination coefficient (R2), slope (m), bias factor (BF), accuracy factor (AF), the objective function (Φ-factor), and f-testing. Therefore, the Stannard (ST) model was good agreement with the actual biomass production (X), ethanol production (P), and sugar consumption (S) data (RSS = 0.22, 6.23, and 45.70 g/L; RMSE = 0.17, 0.88, and 2.39 g/L; MAE = 0.14, 0.64, and 1.72 g/L; R2 = 0.9948, 0.9977, and 0.9972; m = 1.03, 1.02, and 1.02; BF = 1.35, 1.08, and 0.97; AF = 1.41, 1.14, and 1.04; and Φ-factor = 0.008, 0.004, and 0.005 (∑Φ-factor = 0.017) for X, P, and S, respectively). In the prediction of kinetic parameters belonging to the experimental fermentation, the ST model also gave better, satisfactory, and well-directed results than the other mathematical models. Besides, the ST model was also accomplishedly validated using two independent sets of the experimental data yielded from the different carbon sources in various concentrations. Consequently, the models proposed for X, P, and S can serve as universal functions to predict the real values and the kinetic parameters of the ethanol fermentation. Besides, these models can be applied to improve the ethanol fermentation in the ICSTR with CEM.

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Funding

This study was funded by the Akdeniz University Research Foundation (grant number 2012.02.0121.012).

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Correspondence to Irfan Turhan.

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Yatmaz, E., Germec, M., Erkan, S.B. et al. Modeling of ethanol fermentation from carob extract–based medium by using Saccharomyces cerevisiae in the immobilized-cell stirred tank bioreactor. Biomass Conv. Bioref. 12, 5241–5255 (2022). https://doi.org/10.1007/s13399-020-01154-6

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