Application of an integrated statistical design to optimize the cold enzyme hydrolysis conditions for ethanol production

Cold enzyme hydrolysis was investigated on the ethanol production by Saccharomyces cerevisiae during simultaneous saccharification and fermentation (SSF) processing. An integrated statistical design, which incorporated single factor design, response surface methodology (RSM) and weighting coefficient method, was used to determine the optimum hydrolysis conditions leading to maximum biomass, ethanol concentration and starch utilization ratio. After the studied ranges of α-amylase, glucoamylase and liquefaction time were identified by single factor design, RSM was used to further optimize the hydrolysis conditions for each objective. The results showed that, under hydrolysis condition optimized with RSM, biomass, ethanol concentration and starch utilization ratio reached 4.401 ± 0.042 × 10⁸ cells/ml, 14.81 ± 0.23% (wt.%) and 94.52 ± 0.53%, respectively. Finally, multi-objective optimization (MOO) was applied to obtain a compromised result of three desirable responses by weighting coefficient methodology. Biomass of 4.331 ± 0.038 × 10⁸ cells/ml, ethanol concentration of 14.12 ± 0.21% (wt.%) and starch utilization ratio of 92.88 ± 0.21% were simultaneous obtained when hydrolysis at pH 5.9 for 114 min with 233 IU/g_starch α-amylase and 778 IU/g_starch glucoamylase. The optimized conditions were shown to be feasible and reliable through verification tests.