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Modelling of Molasses Fermentation for Bioethanol Production: A Comparative Investigation of Monod and Andrews Models Accuracy Assessment

Authors :
Hamid Zentou
Zurina Zainal Abidin
Robiah Yunus
Dayang Radiah Awang Biak
Mustapha Zouanti
Abdelkader Hassani
Source :
Biomolecules, Vol 9, Iss 8, p 308 (2019)
Publication Year :
2019
Publisher :
MDPI AG, 2019.

Abstract

Modelling has recently become a key tool to promote the bioethanol industry and to optimise the fermentation process to be easily integrated into the industrial sector. In this context, this study aims at investigating the applicability of two mathematical models (Andrews and Monod) for molasses fermentation. The kinetics parameters for Monod and Andrews were estimated from experimental data using Matlab and OriginLab software. The models were simulated and compared with another set of experimental data that was not used for parameters’ estimation. The results of modelling showed that μmax = 0.179 1/h and Ks = 11.37 g.L−1 for the Monod model, whereas μmax = 0.508 1/h, Ks = 47.53 g.L−1 and Ki = 181.01 g.L−1 for the Andrews model, which are too close to the values reported in previous studies. The validation of both models showed that the Monod model is more suitable for batch fermentation modelling at a low concentration, where the highest R squared was observed at S0 = 75 g.L−1 with an R squared equal to 0.99956, 0.99954, and 0.99859 for the biomass, substrate, and product concentrations, respectively. In contrast, the Andrews model was more accurate at a high initial substrate concentration and the model data showed a good agreement compared to the experimental data of batch fermentation at S0 = 225 g.L−1, which was reflected in a high R squared with values 0.99795, 0.99903, and 0.99962 for the biomass, substrate, and product concentrations respectively.

Details

Language :
English
ISSN :
2218273X
Volume :
9
Issue :
8
Database :
Directory of Open Access Journals
Journal :
Biomolecules
Publication Type :
Academic Journal
Accession number :
edsdoj.16fe8ade3608442ebac7339707b1e6dc
Document Type :
article
Full Text :
https://doi.org/10.3390/biom9080308