Comparison of media formulations used to selectively cultivate Dekkera/Brettanomyces
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
AIMS: The objectives of this research were to (i) optimize the concentration of cycloheximide for use in WL media used in the wine industry and (ii) evaluate Dekkera/Brettanomyces differential medium (DBDM) as a means to detect Dekkera. METHODS AND RESULTS: Dekkera bruxellensis and other yeasts were transferred into WL broths containing 0, 10, 50 or 100 mg l(-1) of cycloheximide. While several grew in 10 mg l(-1) , only Hanseniaspora uvarum, Pichia guillermondii, Schizosaccharomyces pombe and D. bruxellensis tolerated ≥50 mg l(-1) of the antibiotic. On solidified WL media after 8-days incubation, colony sizes of two strains of D. bruxellensis (B1b and ATCC 52905) decreased with increased concentrations of cycloheximide, while others (F3 and P2) were unaffected. Although D. bruxellensis B1b did not grow well on another selective medium, DBDM, colony development was improved by the addition of sterilized red wine. CONCLUSIONS: Of the concentrations tested, 50 mg l(-1) cycloheximide inhibited many grape/wine yeasts yet generally yielded countable colonies of Dekkera (1-2.5 mm diameter). Several strains of Dekkera did not grow well on DBDM, probably due to the lack of an unidentified nutrient(s). SIGNIFICANCE AND IMPACT OF THE STUDY: Better media formulations will improve the detection of Dekkera, thereby increasing microbiological control during winemaking.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 it