Prefatory<i>in silico</i>studies and<i>in vitro</i>insecticidal effect of<i>Nigella sativa</i>(L.) essential oil and its active compound (carvacrol) against the<i>Callosobruchus maculatus</i>adults (Fab), a major pest of chickpea
Bibliographic record
Abstract
Abstract To help discover a reasonable and eco-friendly insecticide, we undertook a study on the insecticidal potential of carvacrol and essential oils extracted by hydrodistillation using a Clevenger apparatus from the plant species Nigella sativa seeds essential oils of Nigella sativa (EONS) on Callosobruchus maculatus adults. Several tests including contact toxicity, repellent effect, topical contact test, and inhalation effect were conducted. Adults of C. maculatus have been exposed to the toxic effects of different concentrations of these essential oils as well as with carvacrol. The results obtained showed that both EONS and carvacrol exhibited a moderate repellent effect (class II) on C . maculatus adults. EONS showed the highest toxicity by inhalation test, with an LD 50 of 13.386 and an LD 95 of 33.186 μL/cm 2 , compared to carvacrol (LD 50 = 21.509 and LD 95 = 38.877 μL/cm 2 ). The EONS by contact test exhibited more toxic effects, with an LD 50 of 23.350 µL/100 g and an LD 95 of 45.315 µL/100 g, compared to carvacrol (LD 50 = 27.853 µL/100 g and LD 95 = 45.184 µL/100 g). For the topical contact test results, carvacrol was more toxic, with an LD 50 of 3.915 and an LD 95 of 7.696 µL/mL, compared to EONS (LD 50 = 14.509 and LD 95 = 25.516 µL/mL). The high toxicity of EONS can be explained by the presence of 25.8% of o -cymene, 8.53% of cyclofenchene, and 7.71% of beta-pinene, as well as 4.6% of carvacrol, in its chemical composition. Unmitigatedly, these data suggest that the essential oils of N. sativa may present a raw material for the development of new bio-insecticidal products against C. maculatus , one of the main pests of stored foodstuffs.
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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) | 0.002 | 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".