Composition and structure of Rosaceae leaf cuticles: insights into crystal formation and secondary alcohol biosynthesis
Bibliographic record
Abstract
BACKGROUND AND AIMS: The cuticle covers and protects aerial plant tissues from biotic and abiotic stressors, due in part to its unique composition of cuticular wax compounds and the presence of epicuticular wax crystals. The shape of these crystals is known to be dictated by specific compounds dominating the wax mixture. This study aimed to elucidate the chemical basis for such structures and understand the underlying wax biosynthetic mechanisms in two Rosaceae subfamilies: Amygdaloideae and Rosoideae. METHODS: Gas chromatography coupled with mass spectrometry and flame ionization detection was used to characterize and quantify the leaf wax constituents of 12 species across two Rosaceae subfamilies. Scanning electron microscopy was used to investigate the leaf surface micromorphology. KEY RESULTS: Total wax amounts varied considerably within and between subfamilies, as did the presence of epicuticular wax crystals. Wax tubules were found exclusively in Amygdaloideae and composed primarily of 10-nonacosanol, whereas elongated, irregular platelets occurred only in Rosoideae and were composed of C31 and C33 aliphatics. Isomer analysis showed that secondary alcohols across subfamilies had a conserved 1:2 asymmetry, with hydroxyl groups on even- and odd-numbered carbons, demonstrating shared biochemistry. Amygdaloideae species primarily accumulated alkane pathway products, namely secondary alcohols. Rosoideae species accumulated more primary alcohol pathway products, and more alkanes than secondary alcohols. CONCLUSIONS: Although preferred biosynthetic mechanisms and wax structures are broadly grouped by subfamily, this organization breaks down at lower taxonomic ranks. In Rosaceae, cuticular biochemistry and structure may be quickly tuned within evolutionary time, reflecting yet unknown functional optimization of the cuticle.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".