Pyruvic Acid and Acetaldehyde Production by Different Strains of<i>Saccharomyces cerevisiae</i>: Relationship with Vitisin A and B Formation in Red Wines
Bibliographic record
Abstract
The production of pyruvate and acetaldehyde by 10 strains of Saccharomyces cerevisiae was monitored during the fermentation of Vitis vinifera L. variety Tempranillo grape must to determine how these compounds might influence the formation of the pyroanthocyanins vitisin A and B (malvidin-3-O-glucoside-pyruvate acid and malvidin-3-O-glucoside-4 vinyl, respectively). Pyruvate and acetaldehyde production patterns were determined for each strain. Pyruvate production reached a maximum on day four of fermentation, while acetaldehyde production was at its peak in the final stages. The correlation between pyruvate production and vitisin A formation was especially strong (R (2) = 0.80) on day 4, when the greatest quantity of pyruvate was found in the medium. The correlation between acetaldehyde production and the formation of vitisin B was strongest (R (2) = 0.81) at the end of fermentation when the acetaldehyde content of the medium was at its highest. Identification and quantification experiments were performed by HPLC-DAD. The identification of the vitisins was confirmed by LC/ESI-MS.
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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) | 0.000 | 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 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".