The effect of supplementation with three commercial inactive dry yeasts on the colour, phenolic compounds, polysaccharides and astringency of a model wine solution and red wine
Bibliographic record
Abstract
BACKGROUND: Nowadays supplementing red wines with commercial inactive dry yeasts is a widespread practice in winemaking because it leads to better balanced wines through increased mouthfeel and smooth astringency. The aim of this article is to study, in a red wine and in a model wine solution, how supplementation with three commercial inactive dry yeasts affects chemical composition and astringency. This will give us a better understanding of the action mechanism involved. RESULTS: The results suggest that this action mechanism is related to two different phenomena. The first is that inactive yeasts release polysaccharides and oligosaccharides which can increase mouthfeel and inhibit interactions between salivary protein and tannins. The second is that they have a direct effect on the precipitation or absorption of proanthocyanidins, especially the larger polymers, which have been described as the most astringent. CONCLUSION: It can be concluded that supplementation with inactive yeasts is indeed a useful tool for smoothing the astringency of red wines. © 2016 Society of Chemical Industry.
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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 | 0.001 |
| 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".