Field and Laboratory Responses of Male Codling Moth (Lepidoptera: Tortricidae) to a Pheromone-Based Attract-and-Kill Strategy
Bibliographic record
Abstract
A case study of a pheromone-based attract-and-kill management strategy for codling moth, Cydia pomonella (L.), was conducted to examine key insect behavioral factors mitigating the possible effectiveness of this strategy. Last Call CM is a newly registered attracticide product that combines the primary component of codling moth sex pheromone with the insecticide permethrin. Studies of competition between pheromone point sources within caged trees showed individual attracticide droplets were significantly more attractive to male moths than calling females. In commercial orchard blocks, marked male moths were recaptured after visiting attracticide droplets applied at rates of 50, 100, and 200 droplets/ha, although no marked moths were recaptured in plots with 500 droplets/ha. This experiment also revealed no significant differences among 0, 50, 100, and 200 droplets/ha in suppressing total catch in female-baited traps, nor were total numbers of females attracting at least one male reduced significantly. In plots with 500 droplets/ha applied, male moth catch was suppressed significantly compared with catches in untreated control plots, and the number of females attracting at least one male was reduced significantly as well. Experiments investigating sublethal physiological effects of attracticide exposure upon mating competency of male codling moths demonstrated male leg autotomy at 1, 24, 48, and 72 h after exposure. Male codling moth at 1, 24, 48, and 72 h after exposure placed near calling virgin females exhibited significant behavioral differences from sham-treated males in courtship and mating. These results clarify some of the possible mechanisms, and strengths and weaknesses of this attract-and-kill management strategy for codling moth.
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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) | 0.001 | 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 | 0.001 |
| 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".