Population density and feeding duration of cabbage looper larvae on tomato plants alter the levels of plant volatile emissions
Bibliographic record
Abstract
BACKGROUND: As part of their indirect defense, plants under herbivore attack release volatile chemicals that attract natural enemies of the herbivore. This is a very well-documented phenomenon. However, relatively few studies have investigated the response of plants to different population levels of herbivores and their feeding duration. RESULTS: Working with larvae of the cabbage looper, Trichoplusia ni (Hübner), and tomato plants, Lycopersicon esculentum Mill cv. clarence, and using an ultrafast gas chromatograph (the zNose™) for volatile analyses, the authors studied the effect of larval density and feeding duration on levels of plant volatile emissions. Intense herbivory caused higher emission levels of the herbivore-induced plant volatiles (HIPVs) (Z)-3-hexenyl acetate, (E)-β-ocimene and β-caryophyllene than those caused by moderate herbivory. When herbivory had ceased following 12-24 h of larval feeding, plants kept releasing HIPVs at a high level for a longer period of time than they did following only 6 h of larval feeding. The plants' slow adjustment in their volatile emissions following prolonged larval feeding might be strategic, as such feeding is more likely to have ceased just temporarily. CONCLUSION: This information may help in the development of a pest monitoring system that is based on herbivore-induced plant 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 | 0.000 | 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".