(315f) Enzyme Selection for Hydrolysis of Lignocellulosic Biomass Coupled with Fermentation

Authors: 
Preisig, H. A., Norwegian University of Science and Technology (NTNU)
Birgen, C., Chemical Engineering, Norwegian University of Science and Technology
The India - Norway collaborative project EcoLodge aims at developing a new, integrated biotechnological production process for butyl butyrate, a promising supplement/substitute for diesel and jet engine fuels. The feedstock, lignocellulosic biomass is enzymatically hydrolyzed to produce C5 and C6 sugars. Further, the sugars are fermented by the bacteria to produce butanol and butyric acid, which are the building blocks of butyl butyrate. Butanol and butyric acid fermentations are developed and optimized separately to achieve high yield.

Major challenges for fermentation of biomass derived sugars are low product yield and high hydrolysis cost (Sun and Cheng, 2002). Exploitation of all the C5 and C6 sugar polymers locked in the lignocellulosic biomass can provide a solution to the low yield problem. However, the hydrolysis of all the polymers requires an optimal enzyme mixture, which is usually need to be tailor made or carefully selected for the specific substrate (Jørgensen et. al., 2007). The challenge of high enzymatic hydrolysis cost is mainly due to the enzyme since utility costs are low owing to mild operating conditions (pH 4.8 and temperature 45 - 50 °C) (Duff and Murray, 1996). Therefore, this paper suggests an optimal enzyme mixture, which yields the most favorable composition of C5 and C6 sugars necessary for high yield butanol and butyric acid fermentations.

Mathematical models and kinetic parameters for bacterial growth on mixed substrates from the literature are employed for simulation of fermentations with varied sugar compositions (Lendemann and Egli, 1998). Various composition values of C5 and C6 sugar mixtures are taken from the literature and used in the model simulations as well for comparison purposes (Van Dyk and Pletschke, 2012). The simulation results illustrate the effect of sugar composition on the fermentation yield; eventually provide the optimal value of the sugar composition and corresponding enzyme mixtures. The approach enables backward knowledge flow, from fermentation to enzymatic hydrolysis, to investigate the optimal process conditions. Therefore, it suggests the optimal enzyme mixture after evaluating the possibilities in terms of the cost, composition and the operating conditions.

References

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