Grape Metabolic Response to Postveraison Water Deficit Is Affected by Interseason Weather Variability
Bibliographic record
Abstract
Postveraison water deficit is a common strategy implemented to improve fruit composition in many wine-growing regions. However, contrasting results are often reported on fruit size and composition, a challenge for generalizing the positive impact of this technique. Our research investigated the effect of water deficit (WD) imposed at veraison on Merlot grapevines, during two experimental seasons (2014-2015). In both years WD resulted in reduced carbon assimilation rates and leaf shedding. However, the treatment effect on the analyzed berry parameters varied between seasons. Modification of skin metabolites was more evident in 2015 than in 2014, despite the similar soil water content and water stress physiological parameters (gas exchange, water potential) recorded in the two experimental years. Higher solar radiation and air temperature in 2015 than in 2014 hint for the involvement of atmospheric parameters in fulfilling the potential effect of WD. Our results suggest that the interaction between water availability and weather conditions plays a crucial role in modulating the grape berry composition.
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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) | 0.000 | 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".