Evolution of Flavanol Glycosides during Red Grape Fermentation
Bibliographic record
Abstract
Monomeric and dimeric flavanol glycosides were quantified by UHPLC-MRM in Syrah (SYR) and Grenache (GRE) grapes and in their corresponding wines for the first time. Quantities were extremely variable depending on grape tissue (seeds or skins) and during fermentation. Overall, 22 monomeric and dimeric mono- and diglycosides were determined with concentrations ranging from 0.7 nanograms to 0.700 micrograms per gram of grape tissue, and 0 to 60 micrograms per liter for wines. The evolution of the glycosides' composition during winemaking suggests that almost all these compounds originate in the grapes themselves and display different extraction kinetics during winemaking. One isomer of the monomeric (epi) flavanol monoglycosides seemed to be biosynthesized by yeasts during wine fermentation. The sharp decrease in concentration of some isomers at the late stages of fermentation or after pressing suggests that some grape glycosidase activities convert these compounds into non-glycosylated flavanols.
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How this classification was reachedexpand
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) | 0.000 | 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 teacher head, 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".