Response surface methodology (RSM) was used to optimize the fermentation medium for enhancing pyruvic acid production by Torulopsis glabrata TP19. In the first step of optimization, with Plackett-Burman design, ammoni...Response surface methodology (RSM) was used to optimize the fermentation medium for enhancing pyruvic acid production by Torulopsis glabrata TP19. In the first step of optimization, with Plackett-Burman design, ammonium sulfate, glucose and nicotinic acid were found to be the important factors affecting pyruvic acid production significantly. In the second step, a 23 full factorial central composite design and RSM were applied to determine the optimal concentration of each significant variable. A second-order polynomial was determined by the multiple regression analysis of the experimental data. The optimum values for the critical components were obtained as follows: ammonium sulfate 0.7498 (10.75 g/L), glucose 0.9383 (109.38 g/L) and nicotinic acid 0.3633 (7.86 mg/L) with a predicted value of maximum pyruvic acid production of 42.2 g/L. Under the optimal conditions, the practical pyruvic acid production was 42.4 g/L. The determination coefficient (R2) was 0.9483, which ensures adequate credibility of the model. By scaling up fermentation from flask to jar fermentor, we obtained promising results.展开更多
文摘Response surface methodology (RSM) was used to optimize the fermentation medium for enhancing pyruvic acid production by Torulopsis glabrata TP19. In the first step of optimization, with Plackett-Burman design, ammonium sulfate, glucose and nicotinic acid were found to be the important factors affecting pyruvic acid production significantly. In the second step, a 23 full factorial central composite design and RSM were applied to determine the optimal concentration of each significant variable. A second-order polynomial was determined by the multiple regression analysis of the experimental data. The optimum values for the critical components were obtained as follows: ammonium sulfate 0.7498 (10.75 g/L), glucose 0.9383 (109.38 g/L) and nicotinic acid 0.3633 (7.86 mg/L) with a predicted value of maximum pyruvic acid production of 42.2 g/L. Under the optimal conditions, the practical pyruvic acid production was 42.4 g/L. The determination coefficient (R2) was 0.9483, which ensures adequate credibility of the model. By scaling up fermentation from flask to jar fermentor, we obtained promising results.
