Malo‐ethanolic fermentation in grape must by recombinant strains of <i>Saccharomyces cerevisiae</i>
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Recombinant strains of Saccharomyces cerevisiae with the ability to reduce wine acidity could have a significant influence on the future production of quality wines, especially in cool climate regions. L-Malic acid and L-tartaric acid contribute largely to the acid content of grapes and wine. The wine yeast S. cerevisiae is unable to effectively degrade L-malic acid, whereas the fission yeast Schizosaccharomyces pombe efficiently degrades high concentrations of L-malic acid by means of a malo-ethanolic fermentation. However, strains of Sz. pombe are not suitable for vinification due to the production of undesirable off-flavours. Heterologous expression of the Sz. pombe malate permease (mae1) and malic enzyme (mae2) genes on plasmids in S. cerevisiae resulted in a recombinant strain of S. cerevisiae that efficiently degraded up to 8 g/l L-malic acid in synthetic grape must and 6.75 g/l L-malic acid in Chardonnay grape must. Furthermore, a strain of S. cerevisiae containing the mae1 and mae2 genes integrated in the genome efficiently degraded 5 g/l of L-malic acid in synthetic and Chenin Blanc grape musts. Furthermore, the malo-alcoholic strains produced higher levels of ethanol during fermentation, which is important for the production of distilled beverages.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 it