TRFLP analysis reveals that fungi rather than bacteria are associated with premature yeast flocculation in brewing
Bibliographic record
Abstract
Premature yeast flocculation (PYF) is a sporadic fermentation problem in the brewing industry that results in incomplete yeast utilization of fermentable sugars in wort. Culture-independent, PCR-based fingerprinting techniques were applied in this study to identify the associations between the occurrence of the PYF problem during brewery fermentation with barley malt-associated microbial communities (both bacteria and fungi). Striking differences in the microbial DNA fingerprint patterns for fungi between PYF positive (PYF +ve) and negative (PYF -ve) barley malts were observed using the terminal restriction fragment length polymorphism (TRFLP) technique. The presence of terminal restriction fragments (TRFs) of 360-460 bp size range, for fungal HaeIII restriction enzyme-derived TRFLP profiles appeared to vary substantially between PYF +ve and PYF -ve samples. The source of the barley malt did not influence the fungal taxa implicated in PYF. TRFLP analysis indicates bacterial taxa are unlikely to be important in causing PYF. Virtual digestion of fungal sequences tentatively linked HaeIII TRFs in the 360-460 bp size range to a diverse range of yeast/yeast-like species. Findings from this study suggest that direct monitoring of barley malt samples using molecular methods could potentially be an efficient and viable alternative for monitoring PYF during brewery fermentations.
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 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".