Optimization of Biodegradation of Long Chain n-Alkanes by Rhodococcus sp. Moj-3449 Using Response Surface Methodology
Bibliographic record
Abstract
Oil spills and subsequent pollution of marine ecosystems are associated with oil exploitation. The ultimate fate of unrecoverable portion of spilled oil is biodegradation by microorganisms. Rhodococcus sp. Moj-3449 has proven ability of growth on aliphatic hydrocarbons. In this study Response Surface Methodology was employed to optimize the biodegradability of Moj-3449 by changing salinity, pH, temperature and n-C16 concentration. The duplicate experiments conducted were based on a 5-levels rotatable and orthogonal central composite design (CCD) done in 2 separate blocks. The effect of each factor and their interactions on the biodegradation of n-C16 revealed that the optimal conditions for the biodegradation are 0 % salinity at pH= 6.97, T=28°C and 52.98 % wt/V n-C16 concentration. Under these conditions, the maximum biodegraded amount was predicted at 45.52 % wt/V out of 52.98 % wt/V. The experimentally obtained biodegradation amount at the optimum condition was 44.27 ±0.07 % wt/V. The ability of the strain to effectively break down long-chain n-alkanes at concentration up to 55 % wt/V shows at that this strain is an outstanding candidate for industrial bioremediation of crude oil spills in marine environment.
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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) | 0.001 | 0.001 |
| 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".