Jasmonates signalling plays a key role in modulating berry terpenes accumulation under water deficit conditions in Vitis vinifera L. (cv. Sangiovese)
Bibliographic record
Abstract
Terpenes are among the most important aroma compounds synthesized in grape berries and vine water status affects their accumulation. Although previous studies showed that exogenous hormones applications significantly affected terpenes accumulation, the signalling network involved in regulating their biosynthesis under drought conditions is still unclear. This experiment imposed several deficit irrigation treatments, to elucidate the role of the endogenous hormones signalling network in regulating berry terpenes biosynthesis under water deficit conditions. Berry monoterpenes increased when water deficit was applied during the green or the lag-phase of berry development. Berry abscisic acid and jasmonic acid concentrations were significantly increased by water deficit, regardless of when it was imposed, whereas salicylic acid showed significant differences between irrigation treatments only at veraison. Under water deficit conditions, correlation analyses suggested that jasmonates may be key hormones regulating the biosynthesis of berry monoterpenes, especially in the glycosylated form. Vines subjected to water deficit before veraison showed increased jasmonic acid and methyl jasmonate levels in berries, with the highest monoterpene concentrations measured in the same berries at harvest. These results suggested that endogenous jasmonates may play a key role in water deficit induced signalling that regulates berry monoterpenes biosynthesis.
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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".