UTILIZATION OF BOX-WILSON EXPERIMENTAL DESIGN MATRIX IN BIOGAS PRODUCTION: A RESPONSE SURFACE APPROACH.

Biogas is a renewable energy comprising mixture of gases produced from organic matter, mostly waste, by mixture of bacteria anaerobically using a digester as a bioreactor. It can be burnt to generate heat, electricity or be used as vehicle fuel. The residual (digestate) can be used as fertilizer. This study was carried out to optimize the temperature of the reactor and biogas yield from three independent variables (K=3) namely waste biomass (yam peel, potato peel, unripe plantain peel, watermelon waste, cabbage waste, bread fruit husk, melon husk and cow dung) as feed stock, pH and retention time designed according to Box-Wilson (1951) experimental design matrix. The three variables were varied, each into five equal spaced levels; feedstock volume (6, 8, 10, 12 and 14) litres; pH (2, 4, 6, 8, 10) and retention time (7, 14, 21, 28, 35) days. The feedstock was fermented inside locally fabricated biodigester for maximum of 35 days. A total of 21 experimental runs were generated and subjected to response surface data analysis using MINITAB (version 11.21). A Central Composite Rotatable Response Surface Design (CCRRSD) model was employed to study the linear, quadratic, and cross product effects of the three variables on the biogas yield and temperature of the reactor. Six-dimensional response surface contour figures were plotted to visualize the effects of process variables on the responses with MATLAB (version R2007b). Results revealed that at variable combinations of 10, 6 and 35 respectively for feedstock volume, pH and retention time, there was maximum biogas yield (4. 42 litres) at temperature (33oC i.e mesophilic temperature). Minimum values of biogas yield (0.95 litres) at temperature (28oC) were equally obtained at variable combinations of 10, 6, 7 respectively for volume of feedstock, pH and retention time. Regression coefficient and ANOVA analysis also revealed significant (P < 0.05) negative linear correlation of pH on the temperature of the reactor and positive correlation of retention time on temperature of the reactor quadratically. The three variables have positive linear and interactive effect on the volume of biogas yield with negative effect on the interaction of feedstock and pH. Coefficient of determination was given as 62.03% and 64.93% with R values of 0.79 and 0.81 for the temperature reactor and volume of the biogas obtained respectively hence the model gave good fit for such optimization.