Autolysis and the duration of ageing on lees independently influence the aroma composition of traditional method sparkling wine
Bibliographic record
Abstract
Background and Aims Yeast autolysis is understood to be primarily responsible for giving traditional method sparkling wines complex and developed aromas. The contribution from ageing the wine itself, however, is less well-established. This study aimed to determine the contribution of autolysis products and compounds associated with wine oxidation and ageing in Vitis vinifera L. Chardonnay and Pinot Noir wines over 24 months. Methods and Results Chardonnay and Pinot Noir base wines were tiraged, or aged with and without primary lees. Volatile composition analyses (HS-SPME/GC/MS and GC/MS/MS) were conducted at 6, 12, and 24 months post-bottling and sensory appraisals at 12 and 24 months. The duration of ageing significantly influenced compositional changes in fermentation-derived and oxidative-flavour-associated compounds. Ageing base wines off or on lees produced similar maturation-associated aroma profiles to sparkling wines irrespective of cultivar. Conclusions The contribution of autolysis products did not feature as strongly as anticipated over 24 months, indicating that compounds associated with wine ageing primarily influenced the aroma of mature sparkling wines. This finding suggests winemakers ageing their wines on lees for 24 months or less should place more emphasis on base wine composition to manipulate the aroma profiles of sparkling wines. Significance of the Study First comparative chemical compositional study of base wines concurrently with sparkling wines.
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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) | 0.001 | 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".