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Record W4317853060 · doi:10.1021/acs.jafc.2c06966

Examining How the Fermentation Medium Influences Thiol Expression and Its Perceived Aroma in Commercial Brewing Yeast Strains

2023· article· en· W4317853060 on OpenAlexaff
Richard W. Molitor, Tobias Fischborn, Laurent Dagan, Thomas H. Shellhammer

Bibliographic record

VenueJournal of Agricultural and Food Chemistry · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFermentation and Sensory Analysis
Canadian institutionsLallemand (Canada)
Fundersnot available
KeywordsAromaBrewingFermentationYeastThiolFood scienceChemistrySaccharomyces cerevisiaeAroma compoundBiochemistryTerpene

Abstract

fetched live from OpenAlex

In Saccharomyces, the IRC7 gene encodes for a cysteine S-conjugate β-lyase enzyme which can release polyfunctional thiols from their cysteinylated precursor forms, thereby promoting thiol aroma in beer. This study examined the thiol production of 10 commercial yeast strains in two different media, a hopped yeast extract–peptone–dextrose (YPD) medium and a 100% barley malt wort to explore how differences in yeast strain and medium conditions influence the release of polyfunctional thiols. 3-Sulfanylhexan-1-ol was most affected by medium conditions, and its concentrations were highest in wort fermentations. The higher nitrogen content and pH of the YPD medium relative to the wort fermentations were notable differences, and significant correlations between these variables and the extent of free thiol production were observed. A strong association existed between polyfunctional thiol concentrations and the fermentation-derived, malt, and hop-derived compounds 2-phenylethanol, β-damascenone, and β-ionone. The sensory impressions of thiol character in beer were influenced by the presence of other aromatic compounds such as esters and terpene alcohols, and aroma attributes such as “tropical” were not the most suitable for describing beers brewed with yeasts that fully express homozygous IRC7 F . Sensory attributes “sweaty”, “vegetal”, and “overripe fruit” were more strongly associated with these strains.

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 score0.952
Threshold uncertainty score0.144

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 head0.050
GPT teacher head0.239
Teacher spread0.189 · 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

Citations10
Published2023
Admission routes1
Has abstractyes

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