Comparison of Efficacy of Pheromone Dispensing Technologies for Controlling the Grape Berry Moth (Lepidoptera: Tortricidae) by Mating Disruption
Bibliographic record
Abstract
The efficacy of 3M Sprayable Pheromone for Grape Berry Moth, BASF RAK 1R pheromone dispensers, Isomate GBM pheromone dispensers, and an insecticide program were compared during two seasons for controlling grape berry moth, Endopiza viteana (Clemens), in Niagara peninsula, Ontario, Canada, vineyards. The average number of E. viteana captured in pheromone-baited traps in plots treated with BASF RAK 1R and Isomate GBM dispensers was reduced by 90-100% compared with the average number captured in insecticide-treated plots, indicating a high level of mating disruption. By contrast, there was no difference in the number of moths captured in plots treated with sprayable pheromone and in plots treated with insecticide during the second flight of 1999, suggesting that the sprayable pheromone did not affect the mate-seeking ability of male moths. During the third flight of 1999, and the three flights of 2000, however, the average number of E. viteana captured in plots treated with sprayable pheromone was reduced by 50-99% compared with the average number captured in insecticide-treated blocks, indicating a moderate-to-high level of mating disruption. There was no detectable difference in feeding injury to grape clusters when E. viteana was controlled using two application rates of a sprayable pheromone formulation, two hand-applied pheromone dispensers, or a conventional, insecticide-control program. The disparity between estimated disruption and crop damage in plots treated with sprayable pheromone during the second flight of 1999 suggests that pheromone-baited traps may not provide a reliable estimate of the level of mating disruption when using sprayable pheromone.
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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 | 0.001 |
| 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".