Cassava Peel Starch as a Raw Material for Polyhydroxyalkanoates Synthesis by <i>Cupriavidus</i> <i>necator</i>
Bibliographic record
Abstract
The environmental problems caused by plastics of fossil origin are well known. To reduce harmful impact on the environment, bacterial-based plastics, such as polyhydroxyalkanoates (PHAs), are a promising solution. Microbial PHAs can be produced using abundant and inexpensive agricultural by-products as raw material. In this study, the potential use of Cupriavidus necator 11599 for the bioconversion of cassava starch into biodegradable PHAs was explored. Although Cupriavidus necator 11599 is a well-known PHA producer, it cannot grow directly on starch. Thus, acid hydrolysis was carried out on the starch extracted from cassava peels to obtain fermentable sugars. Optimal concentration of reducing sugars (RSs) was obtained by hydrolysis of cassava peel starch with sulfuric acid concentrations of 0.4 N and 0.6 N, at 95˚C and 4 h. The hydrolyzed starch was used for PHA production in Erlenmeyer flasks using reducing sugars (RSs) concentrations ranging from 10 g/L to 25 g/L. The best RS concentration 20 g/L and 25 g/L gave 85.13% ± 1.17% and 89.01% ± 2.49% of biomass PHA content and biomass concentrations of 8.18 g/L and 8.32 g/L, respectively in 48 hours. This research demonstrates that cassava peel starch as an inexpensive feedstock could be used for PHA production, paving the way for the use of other starchy materials to make bioplastics.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".