Lavandula dentata L.: Phytochemical Analysis, Antioxidant, Antifungal and Insecticidal Activities of Its Essential Oil
Bibliographic record
Abstract
Antioxidant, antifungal and insecticidal activities of essential oil (EO) extracted from the Moroccan lavender (Lavandula dentata) were investigated and their chemical constituents determined. Gas chromatography with flame ionization detection (GC-FID) and gas chromatography-mass spectrometry analyses (GC-MS) were used to examine the phytochemical composition of EO. Antioxidant potential was examined in vitro by use of three tests: DPPH inhibition, reducing power (FRAP) and total antioxidant capacity (TAC). Antifungal activity was assessed by calculating inhibition of growth of Alternaria alternata, Botrytis cinerea and Fusarium oxysporum. Repellent potential and toxicity of EO by contact and inhalation were performed against Callosobruchus maculatus. Sixteen constituents were detected in the EO of Lavandula dentata. The major component was linalool (45.06%) followed by camphor (15.62%) and borneol (8.28%). EO exhibited a significant antioxidant activity, as measured by DPPH and FRAP assays, with IC50 and EC50 values of 12.95 ± 1.300 mg/mL and 11.88 ± 0.23 mg/mL, respectively. EO of lavender exhibited total antioxidant capacity of 81.28 ± 2.28 mg AAE/g EO. EO of lavender showed an inhibitory effect on mycelial growth against tested fungi and was 100% in the case of B. cinerea. EO caused total mortality of adult C. maculatus from 5 µL/L air with LC50 value of 4.01 µL/L air. Significant reduction in numbers of eggs laid (99.2%) and emergence (100%) was observed in a dose-dependent manner up to maxima of 100% and 99.2%, respectively. EO of lavender also showed a moderate potency to repel insects with a mean of 34.44%. EO of Moroccan Lavandula dentata has potential to be an effective natural agent against free radical damage and could be an environmentally friendly alternative bio-fungicide and bio-insecticide.
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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 | 0.001 | 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".