Optimization of synthetic pheromone blend for use in monitoring <i>Choristoneura rosaceana</i> (Lepidoptera: Tortricidae) in Niagara peninsula, Ontario, apple orchards
Bibliographic record
Abstract
Trapping experiments were carried out in Niagara peninsula, Ontario apple orchards to determine the optimum ratios of synthetic pheromone compounds for use in monitoring the obliquebanded leafroller, <i>Choristoneura rosaceana</i> (Harris) (Leptidoptera: Tortricidae). The mean total number of moths captured in traps baited with rubber stopper lures impregnated with 0.97 mg of the major compound (Z)-11-tetradecenyl acetate (Z11-14:OAc) increased 3–4-fold with the addition of 2% of the minor compound (E)-11-tetradecenyl acetate (E11-14:OAc) and increases to 4 and 8% did not change average catch. The addition of 1–8% of the minor compound (Z)-11-tetradecenol (Z11-14:OH) to lures containing 0.97 mg Z11-14:OAc + 2% E11-14:OAc did not affect average catch. There was a 3.5–3.8-fold increase in catch when 0.97 mg Z11-14:OAc + 2% E11-14:OAc + 1.5% Z11-14:OH was combined with 1% of the minor compound (Z)-11-tetradecenal (Z11-14:Ald). Mean trap catch declined when the relative amount of Z11-14:Ald was ≥4%. There was a 2.3–3.7-fold increase mean trap catch when 0.97 mg Z11-14:OAc + 1.5% mg Z11-14:OH + 1% Z11-14:Ald was combined with 1% E11-14:OAc. There was no increase in catch with additional increases in the relative amount of E11-14:OAc. There was a 1.8–2.3-fold decrease in catch when 2% Z11-14:OH was combined with 0.97 mg Z11-14:OAc + 2% E11-14:OAc + 1% Z11-14:Ald. There was no change in mean trap catch with the addition of greater relative amounts of Z11-14:OH. The results suggest that the optimum blend of synthetic pheromone compounds for use in monitoring <i>C. rosaceana</i> in the Niagara peninsula of Ontario is a blend of the main compound Z11-14:OAc plus the minor compounds in relative amounts of 1% E11-14:OAc, 0–1% Z11-14:OH and 1% Z11-14:Ald.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 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 teacher head, 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".