The efficacy of essential oil of <i>Alpinia calcarata</i> (Rosc.) and its major constituent, 1,8-cineole, as protectants of cowpea against <i>Callosobruchus maculatus</i> (F.) (Coleoptera: Bruchidae)
Bibliographic record
Abstract
The bruchid, Callosobruchus maculatus, (F.) causes major losses during the storage of cowpea seeds [Vigna unguiculata (L.) Walp.] in Sri Lanka. Essential oil was extracted from Alpinia calcarata (Rosc.) and 1,8-cineole, identified as the major constituent of the essential oil, was tested for its potential insecticidal activity against C. maculatus. The adults of C. maculatus were susceptible to both fumigant toxicity and contact and fumigant toxicity of 1,8-cineole and A. calcarata oil. In the fumigant toxicity assay, the LC50 (0.685 g L-1) value of 1,8-cineole was similar to that of A. calcarata oil. However, LC50 values of 0.068 g L-1 and 0.141 g L-1 were obtained for the contact and fumigant toxicity of 1,8-cineole and A. calcarata oil, respectively. Oviposition and F1 adult emergence were significantly inhibited by 1,8-cineole and A. calcarata oil at concentrations higher than 0.80 g L-1 in the fumigant toxicity and 0.123 g L-1 in the contact plus fumigant toxicity. Repellent activity of A. calcarata oil was more potent to C. maculatus than 1,8-cineole at doses ranging from 10 to 40 mg. This study reveals that 1,8-cineole is the most toxic component present in A. calcarata oil, and that the repellent activity of A. calcarata oil could be due to 1,8-cineole as well as the other constituents present in the essential oil. Key words: Callosobruchus maculatus (F.), Alpinia calcarata (Rosc.), 1,8-cineole, essential oils, cowpea
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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".