The role of potent thiols in Chardonnay wine aroma
Bibliographic record
Abstract
Background and Aims Polyfunctional thiols are key aroma compounds in many Sauvignon Blanc wines, but their role in other white cultivars is not clear. Methods and Results A survey of 106 commercial Australian Chardonnay wines found a high concentration of 3-mercaptohexan-1-ol, 3-mercaptohexyl acetate, benzyl mercaptan and 4-mercapto-4-methylpentan-2-one, with nearly all wines having a concentration of all compounds well above their reported sensory detection threshold, and some having a concentration comparable to that found in highly fruity Sauvignon Blanc wines. Wines were made on a research scale from a set of Chardonnay juices sourced from 16 vineyards across Australia. Sensory descriptive analysis combined with quantitative aroma volatile data revealed that several aroma and flavour attributes were related to the concentration of the thiols. Conclusions This study provided evidence that substantial flavour in Chardonnay can be contributed by these thiols. Additionally, consumer acceptance data showed that wines with a higher thiol concentration were liked by most consumers. Significance of the Study This study revealed the importance of polyfunctional thiols in Chardonnay wine.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".