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Modelling of Molasses Fermentation for Bioethanol Production: A Comparative Investigation of Monod and Andrews Models Accuracy Assessment
- 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.
- Subjects :
- bioethanol
modelling
fermentation
molasses
Monod
Andrews
Microbiology
QR1-502
Subjects
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