ABSTRACT

It is widely acknowledged that lignocellulosic biomasses (LCB) are renewable, environmentally friendly energy sources that have the potential to significantly lessen our need on fossil fuels. LCB are made up of cellulose, hemicellulose (which includes glucose, xylose, arabinose, galactose, rhamnose, and mannose), and lignin. Their structure is complicated. Pretreatment at high pressure and temperature is required to break down the lignin and hemicellulose components because of their resilience. Requirement of high enzyme dosage for lignocellulosic biomass hydrolysis is one of the challenges for the viability of the second generation biobutanol technology. Here, an enzyme mixture was developed by partially replacing the cellulase proportion with accessory enzymes (xylanase).

In the hydrolysis experiment, pretreated cassava bagasse samples were mixed with measured amounts of cellulase. Another batch was mixed with a 1:1 ratio of cellulase-xylanase enzyme cocktail. Both batches were placed in a water bath shaker at 50°C. Absorbance readings were taken after 6 and 24 hours using a spectrophotometer to determine the reducing sugar yield, which was then used to calculate the percentage hydrolysis yield.

The readings taken after 6 hours indicated that cellulase alone produced a higher reducing sugar yield and percentage hydrolysis yield compared to the cellulase-xylanase cocktail. This was because the specificity of the enzymes in the cocktail reduced overall hydrolysis efficiency. However, after 24 hours, the cellulase-xylanase cocktail showed a higher reducing sugar yield and percentage hydrolysis yield than cellulase alone. This improvement is attributed to the synergistic effect of both enzymes in the cocktail, demonstrating that enzyme cocktails are more effective for biomass hydrolysis over longer periods.

This study elucidates that presence of even small amounts of oligomers and cellobiose pose a strong inhibition for the enzymes. Therefore, development of an optimal enzyme formulation is a sustainable approach to reduce overall enzyme loading for biomass saccharification