Fermentation of Saccharomyces cerevisiae – Combining kinetic modeling and optimization techniques points out avenues to effective process design
| Autor: | Barbara Kavsek, Stefan Scheiner, Martin Joksch, Johannes Scheiblauer |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
0106 biological sciences
0301 basic medicine Statistics and Probability Calibration (statistics) Computation Process design Saccharomyces cerevisiae Models Biological 01 natural sciences General Biochemistry Genetics and Molecular Biology 03 medical and health sciences Oxygen Consumption 010608 biotechnology Biomass Sensitivity (control systems) Predictability Mathematics Parametric statistics Ethanol General Immunology and Microbiology Systems Biology Applied Mathematics food and beverages General Medicine Models Theoretical Kinetics 030104 developmental biology Research Design Modeling and Simulation Scientific method Calibration Fermentation General Agricultural and Biological Sciences Biological system Reduction (mathematics) |
| Zdroj: | Journal of Theoretical Biology. 453:125-135 |
| ISSN: | 0022-5193 |
| DOI: | 10.1016/j.jtbi.2018.05.016 |
| Popis: | A combined experimental/theoretical approach is presented, for improving the predictability of Saccharomyces cerevisiae fermentations. In particular, a mathematical model was developed explicitly taking into account the main mechanisms of the fermentation process, allowing for continuous computation of key process variables, including the biomass concentration and the respiratory quotient (RQ). For model calibration and experimental validation, batch and fed-batch fermentations were carried out. Comparison of the model-predicted biomass concentrations and RQ developments with the corresponding experimentally recorded values shows a remarkably good agreement for both batch and fed-batch processes, confirming the adequacy of the model. Furthermore, sensitivity studies were performed, in order to identify model parameters whose variations have significant effects on the model predictions: our model responds with significant sensitivity to the variations of only six parameters. These studies provide a valuable basis for model reduction, as also demonstrated in this paper. Finally, optimization-based parametric studies demonstrate how our model can be utilized for improving the efficiency of Saccharomyces cerevisiae fermentations. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Full Text from ScienceDirect