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Modelling of Molasses Fermentation for Bioethanol Production: A Comparative Investigation of Monod and Andrews Models Accuracy Assessment
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 fer...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6723480/ https://www.ncbi.nlm.nih.gov/pubmed/31357463 http://dx.doi.org/10.3390/biom9080308 |
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author | Zentou, Hamid Zainal Abidin, Zurina Yunus, Robiah Awang Biak, Dayang Radiah Zouanti, Mustapha Hassani, Abdelkader |
author_facet | Zentou, Hamid Zainal Abidin, Zurina Yunus, Robiah Awang Biak, Dayang Radiah Zouanti, Mustapha Hassani, Abdelkader |
author_sort | Zentou, Hamid |
collection | PubMed |
description | 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 μ(max) = 0.179 1/h and K(s) = 11.37 g.L(−1) for the Monod model, whereas μ(max) = 0.508 1/h, K(s) = 47.53 g.L(−1) and K(i) = 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 S(0) = 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 S(0) = 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. |
format | Online Article Text |
id | pubmed-6723480 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-67234802019-09-10 Modelling of Molasses Fermentation for Bioethanol Production: A Comparative Investigation of Monod and Andrews Models Accuracy Assessment Zentou, Hamid Zainal Abidin, Zurina Yunus, Robiah Awang Biak, Dayang Radiah Zouanti, Mustapha Hassani, Abdelkader Biomolecules Article 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 μ(max) = 0.179 1/h and K(s) = 11.37 g.L(−1) for the Monod model, whereas μ(max) = 0.508 1/h, K(s) = 47.53 g.L(−1) and K(i) = 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 S(0) = 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 S(0) = 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. MDPI 2019-07-26 /pmc/articles/PMC6723480/ /pubmed/31357463 http://dx.doi.org/10.3390/biom9080308 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Zentou, Hamid Zainal Abidin, Zurina Yunus, Robiah Awang Biak, Dayang Radiah Zouanti, Mustapha Hassani, Abdelkader Modelling of Molasses Fermentation for Bioethanol Production: A Comparative Investigation of Monod and Andrews Models Accuracy Assessment |
title | Modelling of Molasses Fermentation for Bioethanol Production: A Comparative Investigation of Monod and Andrews Models Accuracy Assessment |
title_full | Modelling of Molasses Fermentation for Bioethanol Production: A Comparative Investigation of Monod and Andrews Models Accuracy Assessment |
title_fullStr | Modelling of Molasses Fermentation for Bioethanol Production: A Comparative Investigation of Monod and Andrews Models Accuracy Assessment |
title_full_unstemmed | Modelling of Molasses Fermentation for Bioethanol Production: A Comparative Investigation of Monod and Andrews Models Accuracy Assessment |
title_short | Modelling of Molasses Fermentation for Bioethanol Production: A Comparative Investigation of Monod and Andrews Models Accuracy Assessment |
title_sort | modelling of molasses fermentation for bioethanol production: a comparative investigation of monod and andrews models accuracy assessment |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6723480/ https://www.ncbi.nlm.nih.gov/pubmed/31357463 http://dx.doi.org/10.3390/biom9080308 |
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