Factors Influencing Male <I>Plutella xylostella</I> (Lepidoptera: Plutellidae) Capture Rates in Sex Pheromone-Baited Traps on Canola in Western Canada
Bibliographic record
Abstract
Optimization of male moth trapping rates in sex pheromone-baited traps plays a key role in managing Plutella xylostella (L.). We investigated various ways to increase the attractiveness of pheromone-baited traps to P. xylostella in canola agroecosystems in AB, Canada. Factors tested included pheromone blend and dose, addition of a green leaf volatile to the pheromone at different times during the season, lure type, trap color, and height. The industry standard dose of 100 μg of pheromone (four-component blend) per lure (ConTech Enterprises Inc., Delta, British Columbia [BC], Canada) captured the most moths in the two lure types tested. Traps baited with pheromone released from gray rubber septa captured more males than those baited with red rubber septa. Traps baited with lures in which Z11-16: Ac is the main component attracted significantly more moths than those in which Z11-16: Ald is the main component. The addition of the green leaf volatile, (Z)-3-hexenyl acetate, to pheromone at a range of doses, did not increase moth capture at any point during the canola growing season. Unpainted white traps captured significantly more male moths than pheromone-baited traps that were painted yellow. Trap height had no significant effect on moth capture. Recommendations for monitoring P. xylostella in canola agroecosystems of western Canada include using a pheromone blend with Z11-16: Ac as the main component released from gray rubber septa at a dose of 100 μg.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".