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Record W4390908763 · doi:10.1101/2024.01.15.574562

Temporal and spatial dynamics within the fungal microbiome of grape fermentation

2024· preprint· en· W4390908763 on OpenAlexfundno aff
Cristóbal A. Onetto, Christopher M. Ward, Steven Van Den Heuvel, Laura Hale, Kathleen Cuijvers, Anthony R. Borneman

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2024
Typepreprint
Languageen
FieldAgricultural and Biological Sciences
TopicFermentation and Sensory Analysis
Canadian institutionsnot available
FundersWine AustraliaAustralian GovernmentAlberta Water Research Institute
KeywordsMicrobiomeDynamics (music)FermentationBiologyFood scienceBioinformaticsPhysics

Abstract

fetched live from OpenAlex

Abstract Wine fermentation is a highly complex and competitive environment, imposing harsh selective pressures on fungal community ecology and diversity. The composition of fungal communities inhabiting the surface of grapes will directly impact fermentation progression, wine quality, and contribute to the distinctiveness between wines from different geographical regions. Despite this, the extent of microbial community diversity between geographies, termed ‘microbial terroir,’ remains highly debated. We amassed a large survey of grape spontaneous ferments over six years, encompassing 3105 fungal microbiomes across 14 geographically separated grape-growing regions, and nine grape cultivars. Investigation into the biodiversity of these ferments identified that few high abundance genera form the core of the initial grape microbiome. In line with previous studies, various consistent taxa were linked to specific geographical locations and grape varieties. However, these taxa accounted for a small portion of the overall diversity in the dataset. Through unsupervised clustering, we identified three distinct community types in the grape fungal microbiome, each exhibiting variations in the abundance of key genera. Analysing ferments across temporal and spatial scales revealed significant differences in species richness and compositional heterogeneity between wineries and grape growing regions. However, microbial communities were transient between years in the same winery, regularly transitioning between the three broad community types. We then investigated microbial community composition throughout the fermentative process and observed that initial microbial community composition is predictive of the diversity during the early stages of fermentation, with Hanseniaspora uvarum detected as the main non- Saccharomyces species within this large cohort of samples. Our results help to formulate a clear understanding of the spatial and temporal characteristics of the grape juice fungal microbiome and suggest that these communities are mainly defined by the grape niche and in a minor way shaped by local environmental conditions.

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 score0.764
Threshold uncertainty score0.462

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 head0.012
GPT teacher head0.206
Teacher spread0.194 · 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

Citations2
Published2024
Admission routes1
Has abstractyes

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