Strategies to Enhance Polyhydroxyalkanoate Production from Sugarcane Molasses by <i>Cupriavidus</i> <i>necator</i> 11599
Bibliographic record
Abstract
The production of polyhydroxyalkanoate (PHA) is an opportunity to gradually replace some plastics produced from fossil resources. The use of agro-industrial waste to produce PHA is one of the most efficient techniques, because the cost of production is high. Molasse is waste from the sugar industry. It has already been transformed into PHA via fermentation. But Cupriavidus necator is unable to produce PHA from raw molasse. So, several authors have tried to overcome this problem by pretreating molasse before production. In this study, fermentation was conducted in a shake-flask with Cupriavidus necator. Three types of pretreatments of molasse were conducted to enhance PHA production: i) sulfuric acid pretreatment; ii) enzymatic pretreatment and iii) pretreatment with activated carbon. Molasse pretreated accumulates up to a maximum PHA content of 64.56, 75.64 and 58.14 wt.% respectively with (15:100) ratio for acid, (15:100) ratio for enzyme and (20:100) ratio for activated carbon. The obtained result showed an enhancement of PHA production from sugarcane molasses.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".