Enhancing Biomethane Yield from Microalgal Biomass via Enzymatic Hydrolysis: Optimization and Predictive Modeling Using RSM Approach

This study investigates the optimization of enzymatic hydrolysis for enhancing carbohydrate release from microalgal biomass and its subsequent impact on methane production during anaerobic digestion. Using Response Surface Methodology with a Box–Behnken design comprising 15 experimental runs, the effects of enzyme loading (20–40 mg/gVS), pH (4.5–5.5), and incubation time (24–72 h) were evaluated. A quadratic regression model was developed to predict carbohydrate release, revealing significant interactions between these factors. The optimal conditions for enzymatic hydrolysis were determined to be a cellulase dose of 20 mg/gVS, pH 5.0, and an incubation period of 72 h. The model demonstrated excellent predictive accuracy, with an R2 value of 0.9894 and an adjusted R2 of 0.9704. Enzymatic hydrolysis significantly improved methane and biogas yields, with cumulative production reaching 52.50 mL/gVS and 95.62 mL/gVS, respectively, compared to 6.98 mL/gVS and 20.94 mL/gVS for untreated samples. The findings highlight the importance of optimizing enzyme loading and reaction time, while pH variations within the studied range had minimal impact. This study underscores the potential of enzymatic hydrolysis to enhance the bioavailability of organic matter, thereby improving the efficiency of anaerobic digestion for biogas production.