Process Optimization for Ultrasound-Assisted Starch Production from Cassava (Manihot esculenta Crantz) Using Response Surface Methodology

Abstract

Ultrasound-assisted extraction (UAE) has been optimized to improve the current cassava starch production by conventional maceration for the extraction method. Evaluation of several extraction parameters disclosed significant effects (p < 0.05) by three studied factors (ultrasound power, x1; pulse duty-cycle, x2; and solvent to sample ratio, x3). Subsequently, a Box-Behnken design (BBD) in conjunction with response surface methodology (RSM) was employed to optimise the three factors at three levels: x1 (30, 60, 90%), x2 (0.3, 0.6, 0.9 s−1), and x3 (10:1, 20:1, 30:1). The model built for the RSM was validated through the coefficient of determination (R2 > 0.95), prediction error (2.12%), and lack-of-fit (0.71) values. The model validation suggested that the RSM was adequate for the observed data at the 95.0% confidence level. The optimum yield of cassava starch extraction was achieved by applying 90% for ultrasound power, pulse duty-cycle of 1.0 s−1, and solvent to sample ratio of 30:1 with 10 min extraction time. Finally, the UAE produced starch with a purity of 88.36% and a lower viscosity than the commercial sample due to the granules’ size alteration. Hence, apart from speeding up the extraction process, UAE was worthwhile for the starch modification that could maintain the viscosity at a lower value (1920 cP) than the commercial starch (1996 cP) at the highest studied temperature treatment of 70 °C.