Deterrent Effects of Four Neem-Based Formulations on Gravid Female Boll Weevil (Coleoptera: Curculionidae) Feeding and Oviposition on Cotton Squares
Bibliographic record
Abstract
Three commercial neem-based insecticides, Agroneem, Ecozin, and Neemix, and a neem seed extract formulation, bitters, containing 1,036, 16,506, 471, and 223 microg/ml azadirachtin, respectively, were assessed for feeding and oviposition deterrence against gravid female boll weevils, Anthonomus grandis grandis Boheman, in the laboratory. In choice assays, excised cotton squares dipped in the separate formulations were first physically contacted by the weevils' tarsi or antennae fewer times than nontreated control squares. In choice and no-choice assays, each formulation repelled the weevils for > or = 90 min. After 24 h in the choice assays, feeding punctures on the squares treated with Agroneem, Ecozin, or bitters were significantly fewer compared with controls. Egg punctures on the Ecozin- and the bitters-treated squares were significantly fewer than on control squares after 24 h. In the no-choice assay, no significant difference was detected. Aging the formulations under outdoor conditions for 24 h before weevils were exposed resulted in 46-60% and 62-82% reductions in feeding and oviposition punctures, respectively, compared with controls. Agroneem- and bitters-treated squares had > 37% fewer feeding punctures after being aged for 48 h. No significant difference was detected after 72 h of aging. Because the deterrence of the gravid female boll weevils was not correlated with amounts of azadirachtin, azadirachtin does not seem to be the only, or the most influential, component of neem that induced the observed deterrence.
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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".