Hybridization of Selected Nigerian Lignocellulosic Biomass Feedstocks for Bioethanol Production: Modeling and Optimization of Pretreatment and Fermentation Process Parameters Using Response Surface Methodology.

In this study, hybridized feedstocks (mixtures of biomass) of cassava peels plus yam peels, as well as corn cobs plus rice husks biomass, were optimized using the response surface methodology centered on the statistical design of experiments (DOE) of the Box-Behnken design (BBD), to produce bioethanol. The feedstocks were locally sourced, hybridized (mixed), pretreated, and fermented before being distilled in a UOP3CC continuous distillation column. The BBD was applied using a 3-level, 3-factor process variables using pH, time, and particle size, and indicated as X1, X2, and X3, respectively. The bioethanol yield from the two hybridized biomass feedstocks was predicted by the developed quadratic polynomial models from BBD. For the hybridized biomass mixture of cassava peels plus yam peels, the optimal condition was statistically predicted as pH 5.00, fermentation time of 120.00 hours, and particle size of 362.5 microns, the predicted bioethanol yield under the optimal condition was 115.75 mL per 1500 g of hybridized biomass and the average volume of bioethanol obtained was 125.00 mL per 1500 g of biomass, which is within the projected range of the model equation, same applies to rice husks plus corn cobs hybridized biomass, but with a better prospect for bioethanol production.