Statistical optimization of process conditions for direct bioconversion of sewage treatment plant sludge for bioethanol production

The production of bioethanol was conducted by utilizing domestic wastewater sludge as major substrate with the aid of yeast, Saccharomyces cerevisiae using liquid state bioconversion method (submerged fermentation). The optimization of process conditions such as temperature, initial pH, inoculum dosage and agitation was carried out by using the central composite design (CCD) formulated by a statistical optimization software MINITAB. Optimization of process conditions was done with different ranges of temperature, pH, inoculum sizes and agitations with fixed media compositions obtained from previous study. A polynomial regression model was developed to determine the optimum compositions. Several techniques such ANOVA, t-test, p-values were observed to evaluate the model as well as the optimization process. The maximum ethanol production (9.1% v/v) was found while model equation predicted ethanol production with 11.9% v/v U sing the optimum conditions: temperature of 33(0)C, pH of 7, agitation of 200 rpm and inoculum of 1%. The results indicated that the temperature was highly significant (p < 0.01) followed by the pH (p < 0.01), inoculum (p < 0.05) and agitation rate (p < 0.05). The coefficient of determination (R-2) was 90.1% which satisfied the adjustment of experimental data in the model.