Abstract

Central composite experimental design together with response surface methodology (RSM) was employed to optimize the fermentation temperature, pH and inoculums size for maximum production of ethanol and minimum production of volatile acidity during alcoholic fermentation of blueberry wine. A second-order polynomial model was fitted to the content of ethanol and volatile acidity of runs as the responses. Analysis of variance revealed that the quadratic models were well adjusted to predict the experimental data. Lack-of-fit tests were not significant and determination coefficients (R²) were higher than 92.33%. Through the statistically designed optimization, the optimal condition of alcoholic fermentation including temperature of 22.65°C, pH of 3.53 and inoculums size of 7.37% were found. Under this optimal condition, the production of ethanol and volatile acid of blueberry wine could be achieved reaching up to 7.63% and 0.34 g l^-1, respectively. The wine obtained using optimum fermentation conditions was the favorite choice of consumers.

Key words: Blueberry wine, ethanol, fermentation, response surface methodology, yeast.