Production of surfactin by <scp> <i>Bacillus subtilis</i> LAMI005 </scp> and evaluation of its potential as tensoactive and emulsifier
Bibliographic record
Abstract
Abstract In this study, the kinetic of lipopeptide biosurfactant production by Bacillus subtilis LAMI005 and its tensoactive and emulsifier properties were evaluated. The influence of the concentrations of nitrogen ((NH 4 ) 2 SO 4 ) and carbon source (glucose and fructose) on biosurfactant production, using a mineral medium, were evaluated. A production of about 930 mg · L −1 of surfactin was observed for mineral medium supplied with total reducing sugars (16.55 g · L −1 ) and (NH 4 ) 2 SO 4 (1 g · L −1 ) as carbon and nitrogen sources, respectively. The crude biosurfactant exhibited its potential as tensoactive, presenting the capability to reach surface tension of about 28 mN ⋅ m −1 for water and exhibiting low CMC (~14–20 mg · L −1 ). The analysis of emulsifying activity showed a greater stability of emulsion formed in motor oil (3.5 U), soybean oil (2.0 U), and biodiesel (1.5 U). The emulsion formulated on motor oil remained stable for more than 200 h, which was explained by its average drop diameter (~0–10 μm). The surface‐active properties of surfactin did not seem to be affected by different NaCl concentrations, which may promote its applicability in high salt environments, such as oil spills in marine areas.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".