초록
<P><B>Abstract</B></P> <P>A combined experimental/theoretical approach is presented, for improving the predictability of <I>Saccharomyces cerevisiae</I> 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 <I>Saccharomyces cerevisiae</I> fermentations.</P> <P><B>Highlights</B></P> <P> <UL> <LI> A mathematical model of Saccharomyces cerevisiae fermentation is developed. </LI> <LI> The model allows for continuous prediction of the respiration quotient. </LI> <LI> Model predictions for batch and fed-batch processes agree well with experiments. </LI> <LI> Parameters are revealed to which the model responds sensitively. </LI> <LI> Numerical studies show how the model can be utilized for fermentation process design. </LI> </UL> </P>