Modeling simultaneous saccharification and fermentation of softwood

Area of Science:

• Biotechnology
• Biochemical Engineering
• Renewable Energy

Background:

• Simultaneous saccharification and fermentation (SSF) models have been developed for wood substrates.
• Previous models have not been evaluated using pretreated softwood, a key lignocellulosic biomass.

Purpose of the Study:

• To evaluate and adapt an existing mathematical model for SSF using pretreated softwood.
• To assess the model's predictive accuracy for glucose and ethanol concentrations during softwood SSF.

Main Methods:

• Utilized lab-scale batch SSF data from SO2-impregnated, steam-pretreated spruce chips.
• Employed a modified nonlinear, coupled ordinary differential equation model solved numerically.
• Performed parameter estimation using least-squares minimization, incorporating assumptions to address data limitations (e.g., lack of cellobiose measurements).

Main Results:

• The modified model demonstrated good agreement with measured glucose and ethanol concentrations.
• Model simulations confirmed the applicability of its core features to softwood SSF.
• The model predicted enzyme rate saturation at higher concentrations, though this was not experimentally observed within the tested range.

Conclusions:

• The evaluated mathematical model is suitable for describing simultaneous saccharification and fermentation of pretreated softwood.
• Further experimental data, particularly at higher enzyme loadings, is needed to fully validate model predictions regarding enzyme saturation kinetics.