Toxicity and Antifeedant Activity of Calotropis gigantea L. Leaf Extract Against Plutella xylostella L. (Lepidoptera: Plutellidae)
Bibliographic record
Abstract
Many parts of the Calotropis gigantea plant are known to contain bioactive compounds, but leaves contain the most. This study aimed to determine the toxicity and antifeedant activity of C. gigantea leaves against Plutella xylostella. The study was carried out from November 2019 to July 2020. Toxicity was tested using the leaf dipping and spraying methods. Antifeedant activity was tested using a no-choice test and a choice test. Identification of the compound composition of the leaf extract of C. gigantea was carried out at the Integrated Research and Testing Laboratory, Gadjah Mada University. Extract toxicity data obtained were analyzed by Probit analysis. The results showed that the antifeedant activity of C. gigantea leaf extract a no-choice and with choice at each concentration had a significant effect on the consumption of P. xylostella larvae rations. The toxicity (LC50) of the leaf extract of C. gigantea to P. xylostella by the dipping method was 2,958 µgl-1 while the spraying application was 3.944 µgl-1. The composition of chemical compounds contained in the leaf extract of C. gigantea is saponins, alkaloids, flavonoids, tannins, phenols, terpenoids. With the composition of these chemical compounds, the leaf extract of C. gigantea has the potential as a source of vegetable insecticide compounds against P. xylostella.
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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) | 0.001 | 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".