Optimization of enzymatic hydrolysis of bamboo biomass for enhanced saccharification of cellulose through Taguchi orthogonal design

Conversion of raw lignocellulosic biomass is a challenge when the processes have to be carried out on a larger scale in industrial units for bioethanol production. Hence, sustainable biomass processing technologies are essential to attain higher productivity at reduced operational costs. For this purpose, optimization of process parameters of enzymatic hydrolysis of Bambusa bambos was carried out using commercially available cellulase. The effect of different physicochemical parameters such as pH, temperature, enzyme/substrate ratio, mixing speed, and feed particle size was investigated. To analyze their effect on enzymatic hydrolysis and to find optimum values of these parameters, the Taguchi method of optimization was utilized. Five factors pH (4-7), temperature (32 56 degrees C), enzyme/substrate ratio (5-20 %), mixing speed (0 180 rpm) and particle size (60 240 mu M) with four levels produced L16 orthogonal Taguchi experimental design. Experiments were performed as per design and responses were analyzed in terms of glucose production. The optimum response (132.67 mg/dl of glucose) was found at pH 5, temperature 48 degrees C, enzyme/substrate ratio of 20 %, zero mixing speed, and 60 mu M particle size. Enzyme/substrate ratio and pH exhibited more contribution to optimum response than mixing speed and particle size. Thus, we recommend that operate the enzymatic hydrolysis at lower mixing speed and particle size to economize the process while handling higher solid loadings.

Automated summary

This study investigated the enzymatic hydrolysis of Bambusa bambos under different physicochemical parameters and optimized the process using the Taguchi method. The optimal conditions for glucose production were found to be pH 5, temperature 48 degrees C, enzyme/substrate ratio of 20 %, zero mixing speed, and particle size of 60 mu M. Enzyme/substrate ratio and pH were identified as having a greater contribution to the optimal response compared to mixing speed and particle size, suggesting that lower mixing speed and particle size can help economize the process while handling higher solid loadings.