Chrysanthemum expressing a linalool synthase gene ‘smells good’, but ‘tastes bad’ to western flower thrips
Bibliographic record
Abstract
Herbivore-induced plant volatiles are often involved in direct and indirect plant defence against herbivores. Linalool is a common floral scent and found to be released from leaves by many plants after herbivore attack. In this study, a linalool/nerolidol synthase, FaNES1, was overexpressed in the plastids of chrysanthemum plants (Chrysanthemum morifolium). The volatiles of FaNES1 chrysanthemum leaves were strongly dominated by linalool, but they also emitted small amount of the C11-homoterpene, (3E)-4,8-dimethyl-1,3,7-nonatriene, a derivative of nerolidol. Four nonvolatile linalool glycosides in methanolic extracts were found to be significantly increased in the leaves of FaNES1 plants compared to wild-type plants. They were putatively identified by LC-MS-MS as two linalool-malonyl-hexoses, a linalool-pentose-hexose and a glycoside of hydroxy-linalool. A leaf-disc dual-choice assay with western flower thrips (WFT, Frankliniella occidentalis) showed, initially during the first 15 min of WFT release, that FaNES1 plants were significantly preferred. This gradually reversed into significant preference for the control, however, at 20-28 h after WFT release. The initial preference was shown to be based on the linalool odour of FaNES1 plants by olfactory dual-choice assays using paper discs emitting pure linalool at similar rates as leaf discs. The reversal of preference into deterrence could be explained by the initial nonvolatile composition of the FaNES1 plants, as methanolic extracts were less preferred by WFT. Considering the common occurrence of linalool and its glycosides in plant tissues, it suggests that plants may balance attractive fragrance with 'poor taste' using the same precursor compound.
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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) | 0.002 | 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".