Field evaluation of botanical insecticides for the management of Helicoverpa armigera
Bibliographic record
Abstract
AbstractTraditional chemical insecticides have been effective against cotton bollworm Helicoverpa armigera, but have raised concerns over environmental impact and resistance development. This explores the application of botanical insecticides, particularly neem and pyrethrin formulations, as alternatives to chemicals in the management of H. armigera. The use of botanical insecticides is gaining importance due to their lower toxicity to non-target organisms and reduced environmental footprint. Field trials conducted over multiple growing seasons showed that neem-based insecticides effectively reduced larval populations by up to 65.7%, while pyrethrin formulations achieved a 60% reduction. Additionally, both treatments resulted in significant improvements in crop yields and minimized feeding damage, with neem-based products increasing yields by approximately 31.6%. Importantly, botanical insecticides exhibited minimal impact on beneficial insect populations compared to synthetic alternatives. The findings underscore the viability of botanical insecticides as effective tools for managing H. armigera while promoting sustainable agricultural practices. The integration of these eco-friendly products into pest management strategies not only enhances crop protection but also contributes to the preservation of beneficial insects, highlighting their importance in integrated pest management (IPM) programs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 teacher head, 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".