Formation of Hydrogen Sulfide in Wine: Interactions between Copper and Sulfur Dioxide
Bibliographic record
Abstract
The combined synergistic effects of copper (Cu(2+)) and sulfur dioxide (SO₂) on the formation of hydrogen sulfide (H₂S) in Verdelho and Shiraz wine samples post-bottling was studied over a 12-month period. The combined treatment of Cu(2+) and SO₂ significantly increased H₂S formation in Verdelho wines samples that were not previously treated with either Cu(2+) or SO₂. The formation of H₂S produced through Cu(2+) mediated reactions was likely either: (a) directly through the interaction of SO₂ with either Cu(2+) or H₂S; or (b) indirectly through the interaction of SO₂ with other wine matrix compounds. To gain better understanding of the mechanisms responsible for the significant increases in H₂S concentration in the Verdelho samples, the interaction between Cu(2+) and SO₂ was studied in a model wine matrix with and without the presence of a representative thiol quenching compound (4-methylbenzoquinone, 4MBQ). In these model studies, the importance of naturally occurring wine compounds and wine additives, such as quinones, SO₂, and metal ions, in modulating the formation of H₂S post-bottling was demonstrated. When present in equimolar concentrations a 1:1 ratio of H₂S- and SO₂-catechol adducts were produced. At wine relevant concentrations, however, only SO₂-adducts were produced, reinforcing that the competition reactions of sulfur nucleophiles, such as H₂S and SO₂, with wine matrix compounds play a critical role in modulating final H₂S concentrations in wines.
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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".