Semiochemical‐mediated oviposition behavior by female peachtree borer, <i>Synanthedon exitiosa</i>
Bibliographic record
Abstract
Abstract The peachtree borer, Synanthedon exitiosa (Say) (Lepidoptera: Sesiidae), is an important pest of commercial cultivations of peach trees, Prunus persicae (L.) (Rosaceae). Identification of semiochemicals that mediate host selection by adult S. exitiosa may lead to the development of a new earth‐friendly tactic within integrated programs for control of S. exitiosa. Larvae develop in the phloem of peach trees where their feeding stimulates the production of gum frass, a mixture of tree phloem particles, tree sap (gum), and larval feces (frass). We tested the hypothesis that gum‐frass semiochemicals signal a potential host tree, and induce oviposition by female S. exitiosa. In coupled gas chromatographic‐electroantennographic detection analyses of Porapak Q‐collected gum frass volatiles, 21 compounds elicited responses from male or female S. exitiosa antennae. These compounds included four acids, four hydrocarbons, four ketones, three acetates, two aldehydes, γ‐decalactone, conophthorin, 2‐phenylethanol, and 2‐isopropyl‐3‐methoxypyrazine. In dual‐choice laboratory experiments, all groups of compounds, except the acetates, were needed to induce significantly more egg laying by female S. exitiosa on treatment than on unbaited control oviposition sites. By responding to gum frass semiochemicals, female S. exitiosa seem to exploit signals that are complex, detectable, and that reliably indicate a potential host tree for larval development.
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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".