On the basis of knowledge of the biological role of glycerol in the redox balance of Saccharomyces cerevisiae, a fermentation strategy was defined to reduce the surplus formation of NADH, responsible for glycerol synthesis. A metabolic model was used to predict the operating conditions that would reduce glycerol production during ethanol fermentation. Experimental validation of the simulation results was done by monitoring the inlet substrate feeding during fed-batch S. cerevisiae cultivation in order to maintain the respiratory quotient (RQ) (defined as the CO 2 production to O 2 consumption ratio) value between 4 and 5. Compared to previous fermentations without glucose monitoring, the final glycerol concentration was successfully decreased. Although RQ-controlled fermentation led to a lower maximum specific ethanol production rate, it was possible to reach a high level of ethanol production: 85 g · liter ؊1 with 1.7 g · liter ؊1 glycerol in 30 h. We showed here that by using a metabolic model as a tool in prediction, it was possible to reduce glycerol production in a very high-performance ethanolic fermentation process.It is well-known that glycerol is a major by-product during alcoholic fermentation in the yeast Saccharomyces cerevisiae. The role of glycerol in the cellular redox balance (5) and in osmoregulation (4, 16) have been reported in the literature. Participating in the cell redox balance, glycerol is produced by Saccharomyces cerevisiae to reoxidize surplus NADH, formed in the synthesis of biomass and secondary fermentation products, to NAD ϩ (5). Two different strategies for modulating the production of glycerol have been reported in the literature. One strategy is to change the operating conditions of the fermentation process (i.e., aeration levels, stress conditions [salts, acids, osmotic stress, heat shock . . .]) (3,4,8,11,12,19,31,40,42); another is to use genetically modified strains. Engineered strains were constructed by overexpressing and repressing components of the glycerol synthesis pathway (14,18,19,21,25).Complementing biochemical and metabolic engineering experimental approaches, mathematical models may also be useful for interpretation and prediction of biochemical processes. Process models consist in coupling mass balance equations at the reactor scale and at the cellular scale (29). Cells can be modeled at different levels: unstructured models on the population level (15, 27) or structured models on the cellular level. The latter can be a compartmental model (41) or a metabolic regulator model (28). Constraints on carbon, energy, and redox potential linked to the metabolic network can be taken into account by a metabolic model that contains a complete set of metabolic pathways involved in biomass synthesis, energy production, substrate degradation, and cometabolite production (30,35).Metabolic flux analysis is generally used to quantify intracellular fluxes in the central metabolism of microorganisms (7,9,11,22,24,43), but it has had a limited impact due to the lack of regulatory...