Application of response surface methodology (RSM) for optimizing methane yield of oxidative pretreated

This study investigated the application of Response Surface Methodology (RSM) for optimizing and predicting methane yield from oxidative pretreated Xyris capensis. Input process parameters of retention time, temperature, and pretreatment condition were considered, with methane yield as the response. The results show that all three process parameters selected significantly influence methane yield, and analysis of variance (ANOVA) indicates that the RSM model is significant for the study. A correlation coefficient (R2) of 0.9071 was recorded, which implies that the model has 91% prediction accuracy. Interactive influence of temperature and retention time, pretreatment and retention time, and pretreatment and temperature were significant to methane release. Optimum conditions for methane release from RSM model are 14 days retention time, 25 °C temperature, and pretreatment condition of 85% H2O2 and 15% H2SO4 with daily optimum methane yield of 32.65 mLCH4 /gVSadded. This study shows that RSM is suitable for methane yield optimization and prediction during the anaerobic digestion of oxidative pretreated lignocellulose substrates