Simultaneous Biosurfactant Production and Hydrocarbon Biodegradation by the Resident Aerobic Bacterial Flora of Oil Production Skimmer Pit at Elevated Temperature and Saline Conditions
Bibliographic record
Abstract
Six aerobic thermo- and halotolerant bacterial isolates from an oil production skimmer pit were evaluated for their ability to produce biosurfactants and degrade petroleum hydrocarbons simultaneously under elevated temperature and saline conditions. Phylogenetic analysis using 16S rRNA sequencing revealed that the six bacterial isolates used in the study (SKP-1, SKP-2, SKP-3, SKP-4, SKP-5 and SKP-6) were most homologous to the gamma-proteobacteria Pseudomonas sp. VS-1, Pseudomonas aeruginosa strain S2QPS8, Serratia marcescens strain A4, Pseudomonas stutzeri, Pseudomonas stutzeri strain RA10 and Pseudomonas stutzeri strain BOD-3 respectively. Using previously sterilized skimmer pit sample as the sole nutrient, carbon and energy sources and at an elevated temperature of 45 0 C and salinity (chloride) level of 6012 mg L -1 , all the bacterial isolates in a mixed culture were able to grow, produce biosurfactants and degrade petroleum hydrocarbons simultaneously by removing about 92% of residual TPH in the skimmer pit within 2 weeks of exposure. This study suggests that in-situ bioremediation procedure using the resident aerobic bacterial flora of the skimmer pit that are thermotolerant and halotolerant can be developed to degrade the petroleum hydrocarbon contaminants in-situ. This bioremediation procedure can be a more attractive and cost effective option than the costly thermal treatment option that is currently in operation in the industry.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".