Traditional Norwegian <i>Kveik</i> Yeasts: Underexplored Domesticated <i>Saccharomyces cerevisiae</i> Yeasts
Bibliographic record
Abstract
Abstract Human activity has resulted in the domestication of Saccharomyces cerevisiae yeasts specifically adapted to beer production. While there is evidence beer yeast domestication was accelerated by industrialization of beer, there also exists a home-brewing culture in western Norway which has passed down yeasts referred to as kveik for generations. This practice has resulted in ale yeasts which are typically highly flocculant, phenolic off flavour negative (POF-), and exhibit a high rate of fermentation, similar to previously characterized lineages of domesticated yeast. Additionally, kveik yeasts are highly temperature tolerant, likely due to the traditional practice of pitching yeast into warm (>30 °C) wort. Here, we characterize kveik yeasts from 9 different Norwegian sources via PCR fingerprinting, phenotypic screens, lab-scale fermentations, and flavour metabolite analysis using HS-SPME-GC-MS. Genetic fingerprinting via interdelta PCR suggests that kveik yeasts form a lineage distinct from other domesticated yeasts. Our analyses confirm that kveik yeasts display hallmarks of domestication such as loss of 4-vinylguaiacol production and high flocculation, and show superior thermotolerance, ethanol tolerance, fermentation rate, and unique flavour metabolite production profiles in comparison to other ale strains, suggesting a broad industrial potential for this group of yeasts.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".