Optimization of pheromone lure and trap design for monitoring the fir coneworm, <i>Dioryctria abietivorella</i>
Bibliographic record
Abstract
Abstract The major components of the sex pheromone of Dioryctria abietivorella (Groté) (Lepidoptera: Pyralidae) were recently identified as (9Z,11E)‐tetradecadien‐1‐yl acetate (9Z,11E‐14:Ac) and a polyunsaturated, long‐chain hydrocarbon (3Z,6Z,9Z,12Z,15Z)‐pentacosapentaene (C25 pentaene). The optimal ratio of these components and the role of potential minor components were not fully determined in the initial short report on the pheromone's identification. We tested different ratios of the two major components loaded into grey halobutyl rubber septum dispensers, placed in sticky traps deployed in conifer breeding arboreta. The optimal ratio of the two components was 200 µg 9Z,11E‐14:Ac to 2000 µg C25 pentaene. (Z)‐9‐Tetradecen‐1‐yl acetate, which had been identified previously in female pheromone gland extracts, and five other potential minor pheromone components, were tested individually as additions to the optimized two‐component lure blend. None of the ternary blends were more attractive than the optimized two‐component blend, at the ratios tested. Two lure adjuvants, a UV stabilizer (Sumisorb 300) and the antioxidant butylated hydroxytoluene, added individually or together, did not affect the attractiveness of the optimized lure blend. The Pherotech diamond sticky trap baited with the optimized lure blend was the most effective trap design among eight types of sticky trap and a bucket style trap that were tested. Traps baited with synthetic lures were as attractive as traps baited with virgin female moths. The optimized two‐component lure blend in the Pherotech diamond trap is recommended for monitoring fir coneworm infestations. The availability of an effective synthetic pheromone opens the possibility for control tactics using mating disruption or attract‐and‐kill techniques.
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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 | 0.000 |
| 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".