Chemical composition, antioxidative and antimicrobial activity of essential oil Ocimum sanctum L.
Bibliographic record
Abstract
Ocimum sanctum L. (Lamiaceae) sin. Ocimum tenuiflorum L. or Tulsi basil is a plant originating from tropical and subtropical areas of India. It is used in both the traditional and official medicine in India. Tulsi is a type of basil that is insufficiently explored and studied in Europe. The goal of this paper is to determine the chemical composition, antioxidative, and antimicrobial activity of the essential oil Ocimum sanctum L. grown in Serbia. The quantity of essential oil in 100 g of herb (v/w) is 0.68%, with 41 components identified in the tested essential oil. The most represented chemical group are sesquiturpene hydrocarbonates with 80.47%. Other groups were much less represented. Sesquiturpene hydrocarbonate ?-cariophyllene is a predominant component in the essential oil with 63.80%. The quantity of tested essential oil needed to achieve 50% of inhibition of DPPH radicals is 0.35 ?g/ml, and it has high potential to neutralize free radicals. The essential oil exhibited antibacterial activity to all tested strains of bacteria, both Gram-positive and Gram-negative. It affected all strains in an inhibitory way in the interval 0.34-41.50 ?l/ml, and in a bactericide way within the range 22.50-124.5 ?l/ml. The most sensitive strains of bacteria are Salmonella typhimurium and Escherichia coli, while Listeria monocytogenes and Enterococus faecalis showed greatest resistance. The essential oil exhibited antifugal activity on all tested fungi. It affected all tested fungi in an inhibitory way in the interval 4.42-8.83 ?l/ml, and in a microbicide way within the range 10.00-50.00 ?l/ml. The most sensitive fungi are: Aspergillus ochraceus, Penicillium ochrochloron and Penicilium funiculosum, while the most resistent one is Aspergillus niger. The tested basil essential oil Ocimum sanctum demonstrated significant antioxidative and antimicrobial effect and may be used as a raw material in food, pharmaceutical and chemical industries.
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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 | 0.001 | 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) | 0.001 | 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".