Response surface methodology for optimization of fermentation process parameters for improving apple wine quality

Abstract

Apple wine is a fermented alcoholic beverage made from apple juice. To ensure optimal apple wine processing performance and premium final product quality, an optimized selection of various parameters for apple wine fermentation process is imperative. This study is aimed at optimizing the fermentation process based on three primary fermentation parameters, including fermentation temperature, initial pH value and inoculum volume, to improve apple wine quality using response surface methodology (RSM) coupled with central composite rotatable design method (CCRD). Based on the experimental data analysis a second order response surface model was developed to describe the relationship between fermentation temperature, initial pH value, and inoculum volume with respect to the sensory score of apple wine. The results of analysis of variance (ANOVA) showed that the model established by response surface quadratic regression was adequate for predicting apple wine quality. It was observed that the quality of apple wine was significantly influenced by fermentation temperature (p ≤ 0.01), followed by initial pH value (p ≤ 0.01) and inoculum volume (p ≤ 0.01). The temperature of 20 °C, initial pH value of 3.6 and inoculum volume of 9 % were found to be the optimal fermentation condition for ensuring premium quality of apple wine.