Increasing PHB production with an industrially scalable hardwood hydrolysate as a carbon source
Bibliographic record
Abstract
In this study, we report an industrially feasible conversion of wood hydrolysate from a pilot-scale forest biorefinery. The wood hydrolysate was compared to a synthetic hydrolysate with a similar content of carbon sources (glucose, xylose, and acetate). To maximize the PHB concentration, high-cell density cultivations were conducted in bioreactors for 52 h using the bacterium Paraburkholderia sacchari IPT 101 LMG 19450. The conversion of wood hydrolysate yielded a maximum PHB concentration of 34.5 g/L, which is among the highest reported for lignocellulose hydrolysates. In comparison, the use of a synthetic hydrolysate resulted in substantially lower PHB concentration (22.0 g/L). This could be attributed to a higher maximum specific growth rate of 0.36 vs. 0.33 per h for cells grown in wood hydrolysate vs. synthetic hydrolysate. For the wood hydrolysate, the final PHB content per cell mass reached 58 % g/g and a maximum PHB productivity of 0.72 g/(Lh), while the synthetic hydrolysate reached 55 % g/g and 0.46 g/(Lh) respectively. Given the increase in bacterial growth and PHB productivity when using the wood hydrolysate, the chosen lignocellulose conversion process is beneficial for subsequent biotechnological conversion to key bioproducts.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".