Chemical Composition of the Epicuticular and Intracuticular Wax Layers on Adaxial Sides of Rosa canina Leaves
Bibliographic record
Abstract
BACKGROUND AND AIMS: The waxy cuticle is the first point of contact for many herbivorous and pathogenic organisms on rose plants. Previous studies have reported the average composition of the combined wax extract from both sides of rose leaves. Recently, the compositions of the waxes on the adaxial and abaxial surfaces of Rosa canina leaves were determined separately. In this paper, a first report is made on the compositions of the epicuticular and intracuticular wax layers of Rosa canina leaves. The methods described enable the determination of which compounds are truly available at the surface for plant-organism interactions. METHODS: An adhesive was used to mechanically strip the epicuticular wax from the adaxial leaf surface and the removal was visually confirmed using scanning electron microscopy. After the epicuticular wax had been removed, the intracuticular wax was then isolated using standard chemical extraction. Gas chromatography, flame ionization detection and mass spectrometry were used to identify and quantify compounds in the separated wax mixtures. KEY RESULTS: The epicuticular wax contained higher concentrations of alkanes and alkyl esters but lower concentrations of primary alcohols and alkenols when compared to the intracuticular wax. In addition, the average chain lengths of these compound classes were higher in the epicuticular wax. Secondary alcohols were found only in the epicuticular layer while triterpenoids were restricted mainly to the intracuticular wax. CONCLUSIONS: A gradient exists between the composition of the epi- and intracuticular wax layers of Rosa canina leaves. This gradient may result from polarity differences, in part caused by differences in chain lengths. The outer wax layer accessible to the phyllosphere showed a unique composition of wax compounds. The ecological consequences from such a gradient may now be probed.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".