Enhanced β-ionone Emission in Arabidopsis Over-expressing <I>AtCCD1</I> Reduces Feeding Damage <I>in vivo</I> by the Crucifer Flea Beetle
Bibliographic record
Abstract
Plant carotenoid derived β-ionone has been shown to have diverse biological effects on some insect herbivores and herbivore parasitoids. In this study, Arabidopsis transgenic plants over-expressing a carotenoid cleavage dioxygenase1 gene (AtCCD1) were generated to test whether β-ionone emissions could be enhanced and used to control feeding by the crucifer flea beetle (Phyllotreta cruciferae Goeze). The transgenic plants exhibited a morphological phenotype indistinguishable from the wild type (WT) control over their complete life cycle. Gas chromatography and mass spectrometry analyses of headspace volatiles collected from 6-wk-old intact flowering plants revealed substantially enhanced β-ionone emission from transgenic plants compared with WT, but no β-ionone enhancement occurred at a young vegetative stage (4-wk-old seedlings). Bioassays in an enclosed environment showed that AtCCD1 over-expression resulted in ≍50% less leaf area damage by flea beetles on transgenic plants compared with WT plants. The mean number of damaged transgenic leaves per plant also was significantly lower in transgenic plants (P<0.05). Our results indicate that AtCCD1 over-expression and induced β-ionone emission might find application in the control of pests for Brassica crops grown in greenhouse operations. Potentially, β-ionone also could be used on crops grown in open-air ecosystems if this allomone is released in sufficient quantities to discourage herbivore foragers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".