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Record W3135264514 · doi:10.1111/ajgw.12484

Volatile aroma composition and sensory profile of Shiraz and Cabernet Sauvignon wines produced with novel<i>Metschnikowia pulcherrima</i>yeast starter cultures

2021· article· en· W3135264514 on OpenAlexfundno aff
Cristián Varela, Caroline Bartel, Damian Espinase Nandorfy, Eleanor Bilogrevic, T. Tran, Anthony Heinrich, T. Balzan, Keren A. Bindon, Anthony R. Borneman

Bibliographic record

VenueAustralian Journal of Grape and Wine Research · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFermentation and Sensory Analysis
Canadian institutionsnot available
FundersWine AustraliaAustralian GovernmentAlberta Water Research Institute
KeywordsWineAromaFood scienceWinemakingAroma of wineYeastFermentationPopulationAroma compoundBiologyEthanol fermentationStarterYeast in winemakingBotanyChemistrySaccharomyces cerevisiaeBiochemistry

Abstract

fetched live from OpenAlex

Background and Aims The use of non-Saccharomyces yeast strains as starter cultures for wine production has become increasingly popular, particularly due to their positive effect on wine composition, colour, aroma and flavour. Here, we characterise the volatile aroma composition and the sensory profile of Shiraz and Cabernet Sauvignon wines produced with novel active dry yeast preparations of Metschnikowia pulcherrima compared to that of reference strains. Methods and Results Winemaking treatments included an uninoculated fermentation, two reference Saccharomyces cerevisiae fermentations, and sequential fermentations inoculated with either M. pulcherrima AWRI1149 or M. pulcherrima AWRI3050 and S. cerevisiae. Amplicon-based internal transcribed spacer phylotyping was used to determine microbial population dynamics during fermentation. Wines were analysed for volatile composition and subjected to sensory analysis. The M. pulcherrima strains survived and dominated in both grape cultivars, and produced distinctive wine volatile profiles depending on the inoculation treatment. These differences in volatiles resulted in significant differences for several sensory attributes. Conclusions Wines made with active dry yeast preparations of M. pulcherrima AWRI1149 and M. pulcherrima AWRI3050 were characterised by increased intensity of desirable sensory attributes and by low scores for negative descriptors. Significance of the Study This work provides winemakers with additional yeast preparations that can shape sensory profile and wine style.

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 score0.753
Threshold uncertainty score0.170

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 head0.069
GPT teacher head0.320
Teacher spread0.252 · 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

Citations23
Published2021
Admission routes1
Has abstractyes

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Same venueAustralian Journal of Grape and Wine ResearchSame topicFermentation and Sensory AnalysisFrench-language works237,207