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Record W6982623019

Interactions between caffeic and caftaric acids, furan-derived aroma compounds, and chitosan during base wine ageing

2023· other· en· W6982623019 on OpenAlexafffund

Bibliographic record

VenueBrock University Digital Repository (Brock University) · 2023
Typeother
Languageen
FieldArts and Humanities
TopicPentecostalism and Christianity Studies
Canadian institutionsBrock University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCaffeic acidWineAromaPolyphenolWine faultChitosan
DOInot available

Abstract

fetched live from OpenAlex

During sparkling wine ageing, chemical changes take place that alter the composition of the wine, creating nutty, roasted, and caramel aromas and flavours not previously detected in young wines. Furan-derived aroma compounds, a group of odor-active chemicals formed during the long-term storage of wine, contribute to these empyreumatic aroma changes. Hydroxycinnamic acids (HCAs) such as caffeic and caftaric acid, known to be responsible for oxidative browning in wine, also influence the formation of furan-derivative aroma compounds in model wine solutions. Additionally, sparkling wine research using chitosan has been shown to influence the formation of furfural, a furan-derivative thought to contribute a caramel aroma to aged wine. This project had three aims: To determine (1) the impact caffeic and caftaric acid have on furan-derived compound formation during base wine storage, (2) the ability of mushroom-derived chitosan to reduce caffeic and caftaric acid concentrations in Pinot noir juice, and (3) to establish whether chitosan added to base wine influences the generation of furan-derived aroma compounds during storage. For Aim 1, Chardonnay (2019) base wine was stored at 15 and 30 °C for 90 days with additions of fructose, caffeic acid, and caftaric acid independently, or in combinations. Results showed that at 15 and 30 °C, furfural increased slightly with 5 mg/L additions of caffeic and caftaric acid. For Aim 2, Pinot noir juice (2021) was stored at 10 °C for 18 hours with 1 g/L additions of < 3 kDa, 250 kDa, and 422 kDa molecular weight (MW) chitosan, before being racked off prior to fermentation. In the finished wine, < 3 kDa chitosan treatment decreased caftaric acid and increased the amino acids, while the 250 kDa chitosan decreased total HCA estimation, turbidity, and brown pigmentation compared to the control. For Aim 3, Pinot noir (2021) base wine was stored at 15 and 30 °C for 90 days with the aforementioned chitosan treatments. All three MW chitosan treatments at 30 °C substantially increased furfural, homofuraneol, and 5-methylfurfural generation relative to the control. At 15 °C, furfural and homofuraneol were also found at greater concentrations in the chitosan-treated wine. Overall results show (1) Slight modulation of furan-derived compounds due to increased caffeic and caftaric acid concentrations, (2) The reduction of caftaric acid by a low MW chitosan prior to fermentation, and (3) An increase in furan-derived compounds in base wine treated with chitosan during short-term storage. The findings of this thesis determined for the first time the influence of HCAs and chitosan on the concentrations of aroma and flavour compounds, with real applications into the acceleration of ageing in sparkling 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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.015
GPT teacher head0.180
Teacher spread0.165 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2023
Admission routes2
Has abstractyes

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