Massive increases in C31 alkane on <i>Zygophyllum xanthoxylum</i> leaves contribute to its excellent abiotic stress tolerance
Bibliographic record
Abstract
BACKGROUND AND AIMS: Desert plants possess excellent water-conservation capacities to survive in extreme environments. Cuticular wax plays a pivotal role in reducing water loss through plant aerial surfaces. However, the role of cuticular wax in water retention by desert plants is poorly understood. METHODS: We investigated leaf epidermal morphology and wax composition of five desert shrubs from north-west China and characterized the wax morphology and composition for the typical xerophyte Zygophyllum xanthoxylum under salt, drought and heat treatments. Moreover, we examined leaf water loss and chlorophyll leaching of Z. xanthoxylum and analysed their relationships with wax composition under the above treatments. KEY RESULTS: The leaf epidermis of Z. xanthoxylum was densely covered by cuticular wax, whereas the other four desert shrubs had trichomes or cuticular folds in addition to cuticular wax. The total amount of cuticular wax on leaves of Z. xanthoxylum and Ammopiptanthus mongolicus was significantly higher than that of the other three shrubs. Strikingly, C31 alkane, the most abundant component, composed >71 % of total alkanes in Z. xanthoxylum, which was higher than for the other four shrubs studied here. Salt, drought and heat treatments resulted in significant increases in the amount of cuticular wax. Of these treatments, the combined drought plus 45 °C treatment led to the largest increase (107 %) in the total amount of cuticular wax, attributable primarily to an increase of 122 % in C31 alkane. Moreover, the proportion of C31 alkane within total alkanes remained >75 % in all the above treatments. Notably, the water loss and chlorophyll leaching were reduced, which was negatively correlated with C31 alkane content. CONCLUSION: Zygophyllum xanthoxylum could serve as a model desert plant for study of the function of cuticular wax in water retention because of its relatively uncomplicated leaf surface and because it accumulates C31 alkane massively to reduce cuticular permeability and resist abiotic stressors.
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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".