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Model-based optimization and scale-up of multi-feed simultaneous saccharification and co-fermentation of steam pre-treated lignocellulose enables high gravity ethanol production.

Wang R, Unrean P, Franzén CJ - Biotechnol Biofuels (2016)

Bottom Line: The combined feeding strategies were systematically compared and optimized using experiments and simulations.The process was reproducible and resulted in 52 g L(-1) ethanol in 10 m(3) scale at the SP Biorefinery Demo Plant.The optimization routine presented in this work can easily be adapted for optimization of other lignocellulose-based fermentation systems.

View Article: PubMed Central - PubMed

Affiliation: Division of Industrial Biotechnology, Department of Biology and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden.

ABSTRACT

Background: High content of water-insoluble solids (WIS) is required for simultaneous saccharification and co-fermentation (SSCF) operations to reach the high ethanol concentrations that meet the techno-economic requirements of industrial-scale production. The fundamental challenges of such processes are related to the high viscosity and inhibitor contents of the medium. Poor mass transfer and inhibition of the yeast lead to decreased ethanol yield, titre and productivity. In the present work, high-solid SSCF of pre-treated wheat straw was carried out by multi-feed SSCF which is a fed-batch process with additions of substrate, enzymes and cells, integrated with yeast propagation and adaptation on the pre-treatment liquor. The combined feeding strategies were systematically compared and optimized using experiments and simulations.

Results: For high-solid SSCF process of SO2-catalyzed steam pre-treated wheat straw, the boosted solubilisation of WIS achieved by having all enzyme loaded at the beginning of the process is crucial for increased rates of both enzymatic hydrolysis and SSCF. A kinetic model was adapted to simulate the release of sugars during separate hydrolysis as well as during SSCF. Feeding of solid substrate to reach the instantaneous WIS content of 13 % (w/w) was carried out when 60 % of the cellulose was hydrolysed, according to simulation results. With this approach, accumulated WIS additions reached more than 20 % (w/w) without encountering mixing problems in a standard bioreactor. Feeding fresh cells to the SSCF reactor maintained the fermentation activity, which otherwise ceased when the ethanol concentration reached 40-45 g L(-1). In lab scale, the optimized multi-feed SSCF produced 57 g L(-1) ethanol in 72 h. The process was reproducible and resulted in 52 g L(-1) ethanol in 10 m(3) scale at the SP Biorefinery Demo Plant.

Conclusions: SSCF of WIS content up to 22 % (w/w) is reproducible and scalable with the multi-feed SSCF configuration and model-aided process design. For simultaneous saccharification and fermentation, the overall efficiency relies on balanced rates of substrate feeding and conversion. Multi-feed SSCF provides the possibilities to balance interdependent rates by systematic optimization of the feeding strategies. The optimization routine presented in this work can easily be adapted for optimization of other lignocellulose-based fermentation systems.

No MeSH data available.


Related in: MedlinePlus

Fitting and validation of enzymatic hydrolysis model. a and b Concentrations of residual WIS (a) and of glucose (b) after fitting the hydrolysis model to batch experiments at 10 % (w/w) WIS using enzyme dosages of 5 (blue), 10 (red) and 15 (green) FPU (g WIS)−1. c–e Validation of the model was carried out by simulating the time course of glucose (squares and dotted lines) and xylose (stars and dashed lines) concentrations in a separate set of experiments using 15 % WIS and 10 FPU (g WIS)−1 in batch mode (c), fed-batch with all enzymes added initially (d) and fed-batch with enzymes added proportionally to substrate (e). Simulations are illustrated in lines and experiments in symbols. The coefficients of regression (R2) are listed in each sub figure
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Fig3: Fitting and validation of enzymatic hydrolysis model. a and b Concentrations of residual WIS (a) and of glucose (b) after fitting the hydrolysis model to batch experiments at 10 % (w/w) WIS using enzyme dosages of 5 (blue), 10 (red) and 15 (green) FPU (g WIS)−1. c–e Validation of the model was carried out by simulating the time course of glucose (squares and dotted lines) and xylose (stars and dashed lines) concentrations in a separate set of experiments using 15 % WIS and 10 FPU (g WIS)−1 in batch mode (c), fed-batch with all enzymes added initially (d) and fed-batch with enzymes added proportionally to substrate (e). Simulations are illustrated in lines and experiments in symbols. The coefficients of regression (R2) are listed in each sub figure

Mentions: 10 % (w/w) WIS batch hydrolysis was carried out in bioreactors at the enzyme dosages 5, 10 and 15 FPU (g WIS)−1. The glucose yield after 96 h of hydrolysis was improved by 20 % when increasing the enzyme dosage from 5 to 10 FPU (g WIS)−1, and a further increase of 9 % was obtained with 15 FPU (g WIS)−1 compared to the 10 FPU case (Fig. 3a, b). Given these results, 10 FPU (g WIS)−1 enzyme dosage was selected for all following studies.Fig. 3


Model-based optimization and scale-up of multi-feed simultaneous saccharification and co-fermentation of steam pre-treated lignocellulose enables high gravity ethanol production.

Wang R, Unrean P, Franzén CJ - Biotechnol Biofuels (2016)

Fitting and validation of enzymatic hydrolysis model. a and b Concentrations of residual WIS (a) and of glucose (b) after fitting the hydrolysis model to batch experiments at 10 % (w/w) WIS using enzyme dosages of 5 (blue), 10 (red) and 15 (green) FPU (g WIS)−1. c–e Validation of the model was carried out by simulating the time course of glucose (squares and dotted lines) and xylose (stars and dashed lines) concentrations in a separate set of experiments using 15 % WIS and 10 FPU (g WIS)−1 in batch mode (c), fed-batch with all enzymes added initially (d) and fed-batch with enzymes added proportionally to substrate (e). Simulations are illustrated in lines and experiments in symbols. The coefficients of regression (R2) are listed in each sub figure
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4835939&req=5

Fig3: Fitting and validation of enzymatic hydrolysis model. a and b Concentrations of residual WIS (a) and of glucose (b) after fitting the hydrolysis model to batch experiments at 10 % (w/w) WIS using enzyme dosages of 5 (blue), 10 (red) and 15 (green) FPU (g WIS)−1. c–e Validation of the model was carried out by simulating the time course of glucose (squares and dotted lines) and xylose (stars and dashed lines) concentrations in a separate set of experiments using 15 % WIS and 10 FPU (g WIS)−1 in batch mode (c), fed-batch with all enzymes added initially (d) and fed-batch with enzymes added proportionally to substrate (e). Simulations are illustrated in lines and experiments in symbols. The coefficients of regression (R2) are listed in each sub figure
Mentions: 10 % (w/w) WIS batch hydrolysis was carried out in bioreactors at the enzyme dosages 5, 10 and 15 FPU (g WIS)−1. The glucose yield after 96 h of hydrolysis was improved by 20 % when increasing the enzyme dosage from 5 to 10 FPU (g WIS)−1, and a further increase of 9 % was obtained with 15 FPU (g WIS)−1 compared to the 10 FPU case (Fig. 3a, b). Given these results, 10 FPU (g WIS)−1 enzyme dosage was selected for all following studies.Fig. 3

Bottom Line: The combined feeding strategies were systematically compared and optimized using experiments and simulations.The process was reproducible and resulted in 52 g L(-1) ethanol in 10 m(3) scale at the SP Biorefinery Demo Plant.The optimization routine presented in this work can easily be adapted for optimization of other lignocellulose-based fermentation systems.

View Article: PubMed Central - PubMed

Affiliation: Division of Industrial Biotechnology, Department of Biology and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden.

ABSTRACT

Background: High content of water-insoluble solids (WIS) is required for simultaneous saccharification and co-fermentation (SSCF) operations to reach the high ethanol concentrations that meet the techno-economic requirements of industrial-scale production. The fundamental challenges of such processes are related to the high viscosity and inhibitor contents of the medium. Poor mass transfer and inhibition of the yeast lead to decreased ethanol yield, titre and productivity. In the present work, high-solid SSCF of pre-treated wheat straw was carried out by multi-feed SSCF which is a fed-batch process with additions of substrate, enzymes and cells, integrated with yeast propagation and adaptation on the pre-treatment liquor. The combined feeding strategies were systematically compared and optimized using experiments and simulations.

Results: For high-solid SSCF process of SO2-catalyzed steam pre-treated wheat straw, the boosted solubilisation of WIS achieved by having all enzyme loaded at the beginning of the process is crucial for increased rates of both enzymatic hydrolysis and SSCF. A kinetic model was adapted to simulate the release of sugars during separate hydrolysis as well as during SSCF. Feeding of solid substrate to reach the instantaneous WIS content of 13 % (w/w) was carried out when 60 % of the cellulose was hydrolysed, according to simulation results. With this approach, accumulated WIS additions reached more than 20 % (w/w) without encountering mixing problems in a standard bioreactor. Feeding fresh cells to the SSCF reactor maintained the fermentation activity, which otherwise ceased when the ethanol concentration reached 40-45 g L(-1). In lab scale, the optimized multi-feed SSCF produced 57 g L(-1) ethanol in 72 h. The process was reproducible and resulted in 52 g L(-1) ethanol in 10 m(3) scale at the SP Biorefinery Demo Plant.

Conclusions: SSCF of WIS content up to 22 % (w/w) is reproducible and scalable with the multi-feed SSCF configuration and model-aided process design. For simultaneous saccharification and fermentation, the overall efficiency relies on balanced rates of substrate feeding and conversion. Multi-feed SSCF provides the possibilities to balance interdependent rates by systematic optimization of the feeding strategies. The optimization routine presented in this work can easily be adapted for optimization of other lignocellulose-based fermentation systems.

No MeSH data available.


Related in: MedlinePlus