Evaluation of the Combined Effects of Enzymatic Treatment and Aging on Lees on the Aroma of Wine from<i>Bombino bianco</i>Grapes
Bibliographic record
Abstract
In this study, two different doses of commercial beta-glucanase enzyme preparation were tested to verify their effect on wines aged on lees. These wines were compared with two samples with no enzymatic treatment. The former was aged on lees (control), and the latter was readily filtered off from the yeast cell biomass (standard). Analysis of variance (one-way ANOVA), the Tukey test, and principal component analysis (PCA) were applied to all of the samples, which were analyzed for aroma composition, along with galacturonic acid, total acidity, pH, and color. Results showed a large number of statistically significant differences among samples. In general, wines treated with beta-glucanase were characterized by higher concentration of many volatile compounds. The presence of lees and even more the exogenous enzymatic action enhanced almost all volatile compounds. Besides the high presence of ethyl esters, it is worth mentioning the behavior of hexanol and trans-3-hexenol, which are strongly enhanced by the presence of lees and by enzymatic treatments.
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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) | 0.001 | 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".