Drought stress modulates cuticular wax composition of the grape berry
Bibliographic record
Abstract
Drought events are a major challenge for many horticultural crops, including grapes, which are often cultivated in dry and warm climates. It is not understood how the cuticle contributes to the grape berry response to water deficit (WD); furthermore, the cuticular waxes and the related biosynthetic pathways are poorly characterized in this fruit. In this study, we identified candidate wax-related genes from the grapevine genome by phylogenetic and transcriptomic analyses. Developmental and stress response expression patterns of these candidates were characterized across pre-existing RNA sequencing data sets and confirmed a high responsiveness of the pathway to environmental stresses. We then characterized the developmental and WD-induced changes in berry cuticular wax composition, and quantified differences in berry transpiration. Cuticular aliphatic wax content was modulated during development and an increase was observed under WD, with wax esters being strongly up-regulated. These compositional changes were related to up-regulated candidate genes of the aliphatic wax biosynthetic pathway, including CER10, CER2, CER3, CER1, CER4, and WSD1. The effect of WD on berry transpiration was not significant. This study indicates that changes in cuticular wax amount and composition are part of the metabolic response of the grape berry to WD, but these changes do not reduce berry transpiration.
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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".