Process design and optimization of bioethanol production from cassava bagasse using statistical design and genetic algorithm

Abstract

Bioethanol production from agro-industrial residues is gaining attention because of the limited production of starch grains and sugarcane, and food–fuel conflict. The aim of the present study is to maximize the bioethanol production using cassava bagasse as a feedstock. Enzymatic liquefaction, by α-amylase, followed by simultaneous saccharification and fermentation (SSF), using glucoamylase and Zymomonas mobilis MTCC 2427, was investigated for bioethanol production from cassava bagasse. The factors influencing ethanol production process were identified and screened for significant factors using Plackett–Burman design. The significant factors (cassava bagasse concentration (10–50 g/L), concentration of α-amylase (5–25% (v/v), and temperature of fermentation (27–37 °C)) were optimized by employing Box–Behnken design and genetic algorithm. The maximum ethanol concentrations of 25.594 g/L and 25.910 g/L were obtained from Box–Behnken design and genetic algorithm, respectively, under optimum conditions. Thus, the study provides valuable insights in utilizing the cost-effective industrial residue, cassava bagasse, for the bioethanol production.