Aromatic Yeasts: Interactions and Implications in Coffee Fermentation Aroma Profiles
Bibliographic record
Abstract
Nontraditional yeasts prevalent in tropical agricultural fermentations such as coffee and cocoa are known to contribute to aroma profiles, yet the functional roles and interactions between the associated microbial consortia in a farm fermentation are unclear. Here, boiled green bean extract (GBE) from green coffee beans was developed as a rich screening medium to deconstruct the microbial consortia and their interactions during the fermentation of dried green coffee beans. When cultivated in coculture with S. cerevisiae on GBE, strain-specific groupings with distinct volatile organic profiles were observed for nontraditional yeasts (e.g., Hanseniaspora spp., Pichia kudriavzevii ). Further changes are evident when constructed consortia composed of nontraditional yeast, S. cerevisiae, and Lactococcus lactis var. cremoris were cultured in GBE, and a comparison with abiotically acidified GBE suggests that pH plays a major role in the influence of lactic acid bacteria (LAB) on fermentation aromas. This approach represents a tool for the development of starter culture formulations to create different flavor profiles in coffee fermentation.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".