Optimizing a pheromone lure for the sugar beet root maggot fly, <i>Tetanops myopaeformis</i>
Bibliographic record
Abstract
Abstract We previously described a putative aggregation pheromone in adults of the sugar beet root maggot, Tetanops myopaeformis (von Röder) (Diptera: Ulidiidae), comprising nine compounds identified from males. Here, we conducted a series of experiments aimed at simplifying the blend of compounds necessary to achieve attraction as well as determining the dose that maximizes captures when formulated into an attractant lure. In all experiments, females showed stronger and more consistent evidence of attraction than males. White sticky traps baited with different blends of pheromone compounds that included the major component, (R)‐(−)‐2‐nonanol, showed significantly higher female captures relative to those baited with blends that excluded the major component. (R)‐(−)‐2‐nonanol alone was at least as effective as any blend that included this compound with other minor pheromone components. Lures using racemic 2‐nonanol were as effective as the (R) enantiomer for both females and males, with some evidence of weak attraction to the (S) enantiomer (which is not produced by males) observed as well. Maximum capture rates using racemic 2‐nonanol were estimated to occur with doses of ca. 795.5 and 621.6 mg for females and males, respectively. Addition of 2‐nonanol lures to standard orange sticky stake traps currently used to monitor flies increased captures of both sexes. The pheromone lure developed here could improve trapping efficiency of current monitoring programs for T. myopaeformis and may also be used to develop other management tools for this important pest of sugar beet.
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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) | 0.000 | 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) | 0.001 | 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".