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Record W2520772528 · doi:10.3390/molecules21091214

Formation of Hydrogen Sulfide in Wine: Interactions between Copper and Sulfur Dioxide

2016· article· en· W2520772528 on OpenAlexfundno aff
Marlize Z. Bekker, Mark E. Smith, Paul A. Smith, Eric Wilkes

Bibliographic record

VenueMolecules · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFermentation and Sensory Analysis
Canadian institutionsnot available
FundersWine AustraliaAustralian GovernmentUniversity of MelbourneAlberta Water Research Institute
KeywordsWineChemistryHydrogen sulfideBottling lineCopperSulfurSulfur dioxideSulfiteCatecholInorganic chemistryWine faultMetalAcetaldehydeOrganic chemistryYeast in winemakingFood scienceBiochemistry

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.477
Threshold uncertainty score0.090

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.021
GPT teacher head0.239
Teacher spread0.218 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations40
Published2016
Admission routes1
Has abstractyes

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