AIM: To study the effect of glucose concentrations on the growth by Brettanomyces bruxellensis yeast strain in batch experiments and develop a mathematical model for kinetic behaviour analysis of yeast growing in batch culture. METHODS AND RESULTS: A Matlab algorithm was developed for the estimation of model parameters. Glucose fermentation by B. bruxellensis was studied by varying its concentration (5, 9.3, 13.8, 16.5, 17.6 and 21.4%). The increase in substrate concentration up to a certain limit was accompanied by an increase in ethanol and biomass production; at a substrate concentration of 50-138 g l(-1), the ethanol and biomass production were 24, 59 and 6.3, 11.4 g l(-1), respectively. However, an increase in glucose concentration to 165 g l(-1) led to a drastic decrease in product formation and substrate utilization. CONCLUSIONS: The model successfully simulated the batch kinetic observed in all cases. The confidence intervals were also estimated at each phase at a 0.95 probability level in a t-Student distribution for f degrees of freedom. The maximum ethanol and biomass yields were obtained with an initial glucose concentration of 138 g l(-1). SIGNIFICANCE AND IMPACT OF THE STUDY: These experiments illustrate the importance of using a mathematical model applied to kinetic behaviour on glucose concentration by B. bruxellensis.
AIM: To study the effect of glucose concentrations on the growth by Brettanomyces bruxellensisyeast strain in batch experiments and develop a mathematical model for kinetic behaviour analysis of yeast growing in batch culture. METHODS AND RESULTS: A Matlab algorithm was developed for the estimation of model parameters. Glucose fermentation by B. bruxellensis was studied by varying its concentration (5, 9.3, 13.8, 16.5, 17.6 and 21.4%). The increase in substrate concentration up to a certain limit was accompanied by an increase in ethanol and biomass production; at a substrate concentration of 50-138 g l(-1), the ethanol and biomass production were 24, 59 and 6.3, 11.4 g l(-1), respectively. However, an increase in glucose concentration to 165 g l(-1) led to a drastic decrease in product formation and substrate utilization. CONCLUSIONS: The model successfully simulated the batch kinetic observed in all cases. The confidence intervals were also estimated at each phase at a 0.95 probability level in a t-Student distribution for f degrees of freedom. The maximum ethanol and biomass yields were obtained with an initial glucose concentration of 138 g l(-1). SIGNIFICANCE AND IMPACT OF THE STUDY: These experiments illustrate the importance of using a mathematical model applied to kinetic behaviour on glucose concentration by B. bruxellensis.