Sustainable polyhydroxybutyrate production in integrated forest biorefineries
Bibliographic record
Abstract
Biopolymers can provide environmentally friendly alternatives to the use of fossil fuel derived polymers. Among others, their production can be net carbon negative and their disposal can help fertilizing soil by composting. However, the environmental benefits of these biopolymers are largely untapped as their overall production capacity is marginal. This low production is primarily caused by their high production cost and selling price, which hinder most biopolymers to compete on the market. One of the most promising, yet expensive biopolymers are the microbiologically produced polyhydroxyalkanoates (PHAs), since they are compostable and also biodegrade in the marine environment. Furthermore, the currently used raw materials for their production (corn starch and vegetable oils) are not only expensive, but also compete with food production. Alternatively, in Canada, wood is abundantly available through the pulp and paper infrastructure, with residues which can be fed to modern biorefineries. This work explores the feasibility of integrating the most well-known PHA, polyhydroxybutyrate (PHB), into forest biorefineries using the bacterium Paraburkholderia sacchari.For this work, the first forest biorefinery scheme was based on the hydrolysis of softwood hemicellulose as a feedstock for PHB production. Softwood cellulose and lignin were recovered to be further converted into other products. Softwood hemicellulose has a favourable composition as compared to most other hemicelluloses, as it has a high share of the six carbon sugars mannose, glucose and galactose. Mannose and galactose were tested as carbon sources for P. sacchari for the first time and showed maximum specific growth rates of 97% and 60% relative to glucose, respectively. However, the presence of inhibitory compounds (acetate, 5 hydroxymethylfurfural, furfural and phenols) inhibited all bacterial growth. It was found that the inhibition comes from strong synergistic effects when the inhibitors are present in mixtures, and the magnitude of the effects was quantified with a mixture design model. Albeit the initial inhibition could be overcome by a high initial cell density (optical density ≥ 5.6) when using a simulated softwood hemicellulose hydrolysate, this approach was not successful for real softwood hemicellulose hydrolysate. Nevertheless, when the hydrolysate was added as a feed solution after an initial growth phase of 24 h, the sugars were all consumed. In comparison with an inhibitor-free hardwood hydrolysate, the growth rate and PHB yield were lower with softwood hemicellulose hydrolysate. While the sugar composition of the hydrolysate was therefore promising for PHB production, the inhibitory effect currently makes it unsuitable as the carbon source.The second biorefinery scheme studied was based on a pilot plant process developed by FPInnovations using hardwood biomass. The process converts hardwood cellulose and hemicellulose into a holocellulose hydrolysate, which was used as carbon source for PHB production. Using this hardwood hydrolysate in shake flask fermentations increased the maximum specific growth rate and PHB accumulation of the bacterium as compared to simulated hydrolysates. In high-cell density bioreactor fermentations, the wood hydrolysate afforded one of the highest PHB concentrations to date from lignocellulosic biomass. The chemical composition, thermal transitions and viscoelastic properties were similar to literature values of PHB. The number average molecular mass was 246.4 kDa with a PDI of 3.29. These results make PHB from hardwood hydrolysate, as co product with H lignin, a sustainable production scheme for industrial PHB production
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".