Computational simulation and statistical analysis of bioethanol production from Madhuca indica by batch fermentation process using Saccharomyces cerevisiae
| Autor: | Gopinath Halder, Shraboni Mukherjee, Madhumanti Mondal, Sohan Dey, Sumit H. Dhawane, Soumya Banerjee, Debaprasad Dutta |
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| Rok vydání: | 2016 |
| Předmět: |
0106 biological sciences
biology Batch fermentation Renewable Energy Sustainability and the Environment business.industry 020209 energy Saccharomyces cerevisiae Energy Engineering and Power Technology 02 engineering and technology Madhuca biology.organism_classification 01 natural sciences Biotechnology Computational simulation Biofuel 010608 biotechnology 0202 electrical engineering electronic engineering information engineering Statistical analysis business Biological system Root-mean-square deviation Mathematics Time profile |
| Zdroj: | Sustainable Energy Technologies and Assessments. 18:16-33 |
| ISSN: | 2213-1388 |
| DOI: | 10.1016/j.seta.2016.09.004 |
| Popis: | Madhuca indica (Mahua flowers) abundantly available in tropical region of India was used to produce bioethanol using Saccharomyces cerevisiae in batch fermentation process. The experiments were investigated at three different initial substrate concentrations at 30 °C for 96 h maintaining pH at 5. A regression analysis on various kinetic models was performed to illustrate the concentration – time evolutions. Each model was analyzed to determine the various constraints like R2, R2adjusted, root mean square deviation (RMSD) and variances for different experimental runs. 4th order Runge-Kutta method was employed to obtain the performance curves to predict its compatibility with experimental profiles. Hinshelwood model fits the concentration time profile most satisfactorily and can predict the bioethanol yield within acceptable error range. Hence, the Hinshelwood model could be applied to predict the bioethanol yield and describe the kinetics of batch fermentation of Madhuca indica. |
| Databáze: | OpenAIRE |
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