Optimizing No-Cook Ethanol Production from Cassava Flour: An Energy-Efficient Approach Using Granular Starch-Hydrolysing Enzymes

Abstract Granular raw starch-hydrolyzing enzymes were applied at low temperatures for ethanol production from cassava flour using no-cook technology under very high gravity (270g/L), lowering energy consumption compared with traditional cooking processes. A Doehlert design optimized this system by evaluating the interactive performance of three key processing factors: dosages of Stargen 002 (glucoamylase and a-amylase), Amigase Mega L (glucoamylase) and yeast cell concentration. The resulting response surface model demonstrated an excellent statistical fit to empirical laboratory data (R2 = 0.977, adjusted R2 = 0.927, predicted R2 = 0.819) with no evidence of lack of fit (p = 0.9083). Both linear (p<0.01) and quadratic effects (p<0.05) for all three independent variables were highly significant. Response surface modeling indicated that volumetric ethanol yield was maximized at 14.4% v/v under optimized input parameters: 2,552 GAU Stargen 002/kg cassava flour, 360 GAU Amigase Mega L/kg cassava flour, a yeast inoculum of 2.87×107 cells/mL, revealing strong synergistic behavior. Under these optimized parameters, a 15-L pilot-scale validation run achieved an actual ethanol concentration of 14.1% v/v, representing 84.0% of the theoretical maximum yield. Our model therefore improves cassava-based no-cook ethanol production at both laboratory and pilot scales by reducing enzyme and yeast requirements. This contributes to a more cost-effective and sustainable system with strong applicability to global cassava biofuel production, supporting greenhouse gas reduction and progress toward carbon neutrality.