Yeast communities of a North American hybrid wine grape differ between organic and conventional vineyards
Bibliographic record
Abstract
AIMS: To compare the species diversity and composition of indigenous yeast communities of hybrid grapes from conventionally and organically cultivated vineyards of an emerging cool-climate wine producing region. METHODS AND RESULTS: Illumina MiSeq sequences from L'Acadie blanc grape musts were processed and filtered to characterize indigenous yeast communities in organic and conventional vineyards of the Annapolis Valley wine region in Nova Scotia, Canada. While cultivation practice was not associated with yeast diversity or species richness, there was a strong effect on yeast community composition, with conventional vineyards characterized by higher proportions of Sporidiobolales and Filobasidium magnum, and organic vineyards supporting Filobasidium species other than F. magnum and higher proportions of Symmetrospora. There was also variation in yeast community composition among individual vineyards, and from year to year. CONCLUSIONS: This is the first comprehensive assessment of yeasts associated with hybrid grapes grown using different cultivation practices in a North American cool climate wine region. Communities were dominated by basidiomycete yeasts and species composition of these yeasts differed significantly between vineyards employing organic and conventional cultivation practices. The role of basidiomycete yeasts in winemaking is not well understood, but some species may influence wine characteristics.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".