Oviposition response of spruce budworm (Lepidoptera: Tortricidae) to host terpenes and green-leaf volatiles
Bibliographic record
Abstract
Abstract A dual-choice behavioral bioassay and gas chromatography – electroantennogram detection (GC–EAD) were used to determine the effect of host terpenes and nonhost green-leaf volatiles (GLVs) on the oviposition preference of the spruce budworm, Choristoneura fumiferana (Clemens). Some emphasis was placed on assessing the ability of females to distinguish between enantiomers of chiral monoterpenes because (+)-α-pinene but not (–)-α-pinene or (±)-α-pinene had been shown previously to promote oviposition. Headspace volatiles from white spruce, Picea glauca (Moench) Voss (Pinaceae), and balsam fir, Abies balsamea (L.) Mill. (Pinaceae), were sampled using solid-phase microextraction and identified by gas chromatography – mass spectrometry with the aid of a chiral column. Females deposited significantly more egg masses on filter paper substrate treated with host monoterpenes than on controls. Contrary to expectation, substrates treated with several GLVs were also preferred over the controls. None of the GLVs or terpenes was deterrent. Females showed no significant ability in either the behavioral or the GC–EAD bioassays to distinguish between enantiomers of selected chiral monoterpenes, including α-pinene, in contrast to earlier findings. We conclude that host terpenes serve as general rather than host-specific oviposition stimuli for spruce budworm.
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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".