Factors controlling inflorescence primordia formation of grapevine: their role in latent bud fruitfulness? A review
Bibliographic record
Abstract
The grapevine (Vitis vinifera L.) is a widely cultivated species of major economic importance for wine production. The quality and quantity of grapes are criteria of prime importance to the wine industry, but they are highly variable from year to year. Unlike many perennial plants, cluster formation unfolds in two seasons: season 1 takes place in the bud until dormancy, and season 2 starts after budbreak in the following year. Season 1 corresponds to the initiation and differentiation of inflorescence primordia, controlled by many exogenous and endogenous factors, which explains up to 60% seasonal variation in yield. Season 2 consists of flowering and fruit development, which explains, respectively, 30% and 10% of seasonal variation in yield. It is therefore essential to understand the impact of these factors to better control the yield. This review aims to summarize past and present knowledge concerning the physiology of latent buds relating to their fruitfulness, and to assess the impact of environmental, hormonal, and regulation factors on the final yield. Avenues of further research to understand physiological, biochemical and molecular regulatory mechanisms of initiation and differentiation of clusters will be then proposed.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".