Development of a Host-Based Semiochemical Lure for Trapping Emerald Ash Borer<i>Agrilus planipennis</i>(Coleoptera: Buprestidae)
Bibliographic record
Abstract
Bark volatiles from green ash Fraxinus pennsylvanica were tested for electrophysiological activity by Agrilus planipennis using gas chromatographic-electroantennographic detection (GC-EAD) and for behavioral activity using baited purple traps in Michigan.GC-EAD analysis of the headspace volatiles of bark tissue samples from 0-and 24-h-old fully girdled (stressed) ash trees showed that the latter had elevated sesquiterpene levels.Six of the elevated compounds consistently elicited antennal responses by both male and female A. planipennis.Five of the antennally active compounds were identiÞed as ␣-cubebene, ␣-copaene, 7-epi-sesquithujene, trans--caryophyllene, and ␣-humulene (␣-caryophyllene).The sixth EAD-active compound remains unidentiÞed.We monitored capture of adult A. planipennis on traps baited with several combinations of ash tree volatiles.Treatments included two natural oil distillates (Manuka and Phoebe oil) that were found to contain, respectively, high concentrations of four and Þve of the six antennally active ash bark volatiles.A four-component leaf lure developed by the USDA Forest Service and Canadian Forest Service was also tested.In three separate Þeld studies, Manuka oilÐ baited traps caught signiÞcantly more adult beetles than unbaited traps.Lures designed to release 5, 50, and 500 mg of Manuka oil per day all caught more insects than unbaited traps.In a Þeld test comparing and combining Phoebe oil with Manuka oil, Phoebe oilÐ baited traps caught signiÞcantly more beetles than either Manuka oilÐ baited traps or unbaited traps.We hypothesize that the improved attractancy of Phoebe oil to A. planipennis over Manuka oil is caused by the presence of the antennally active sesquiterpene, 7-epi-sesquithujene. KEY WORDS Buprestidae, bark volatiles,
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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 | 0.001 | 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".