Technological properties of <i>Enterococcus faecium</i> isolated from ewe's milk and cheese with importance for flavour development
Bibliographic record
Abstract
Eight Enterococcus faecium strains isolated from ewe milk and artisanal cheese from northwest Argentina were screened for biotechnological properties relevant to flavour development. The API ZYM test showed absence of proteases, presence of high amounts of peptidases, and high esterase-lipase activities. Low extracellular proteolytic activity was observed. Most strains produced diacetyl in milk, with E. faecium OvL 214 and OvL 254 being the best producers. Biomass and growth rate increased when citrate was added to the medium, suggesting that these strains could use citrate as a main energy source. After 24 h of incubation, citrate was completely consumed in complex medium supplemented with glucose and citrate. An average of 17% residual citrate was detected in complex media supplemented with citrate. For all strains, esterase activity was detected up to alpha-naphthyl-caproate. They hydrolyzed alpha-naphthyl derivatives of fatty acids in this order: C3 > C6 > C4 > C8 > C2. Post-electrophoretic detection of esterase activities revealed the presence of multiple esterases. Hydrolysis of tributyrin, tricaprylin, and milk fat was observed in cell-free extracts. Enterococcus faecium strains isolated from ewe milk and artisanal cheese from northwest Argentina present the metabolic potential to contribute to cheese flavour development.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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 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".