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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

Overview of attention for article published in Biotechnology for Biofuels, April 2016
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Title
Model-based optimization and scale-up of multi-feed simultaneous saccharification and co-fermentation of steam pre-treated lignocellulose enables high gravity ethanol production
Published in
Biotechnology for Biofuels, April 2016
DOI 10.1186/s13068-016-0500-7
Pubmed ID
Authors

Ruifei Wang, Pornkamol Unrean, Carl Johan Franzén

Abstract

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. 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. 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.

Twitter Demographics

The data shown below were collected from the profiles of 3 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 91 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Mexico 1 1%
Thailand 1 1%
Brazil 1 1%
Unknown 88 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 20 22%
Student > Bachelor 13 14%
Student > Master 11 12%
Researcher 10 11%
Student > Doctoral Student 6 7%
Other 11 12%
Unknown 20 22%
Readers by discipline Count As %
Agricultural and Biological Sciences 15 16%
Chemical Engineering 14 15%
Engineering 13 14%
Biochemistry, Genetics and Molecular Biology 11 12%
Chemistry 4 4%
Other 8 9%
Unknown 26 29%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 06 May 2016.
All research outputs
#3,509,273
of 7,659,635 outputs
Outputs from Biotechnology for Biofuels
#253
of 611 outputs
Outputs of similar age
#121,963
of 267,895 outputs
Outputs of similar age from Biotechnology for Biofuels
#12
of 20 outputs
Altmetric has tracked 7,659,635 research outputs across all sources so far. This one has received more attention than most of these and is in the 51st percentile.
So far Altmetric has tracked 611 research outputs from this source. They receive a mean Attention Score of 3.9. This one has gotten more attention than average, scoring higher than 54% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 267,895 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 51% of its contemporaries.
We're also able to compare this research output to 20 others from the same source and published within six weeks on either side of this one. This one is in the 35th percentile – i.e., 35% of its contemporaries scored the same or lower than it.