Growth of proteinase-positive and proteinase-negative lactococci strains in reconstituted goat and cow milks
Bibliographic record
Abstract
The growth of proteinase-positive Lactococcus lactis strains and the proteinase-negative variants was studied in reconstituted goat and cow milks at 90, 120 and 150 g•kg -1 total solids.pH change and lactic acid production were also compared in the two milks.Goat milk showed a higher buffering capacity than cow milk.The buffering capacity increased with the total solid contents in reconstituted milk.The proteinase-positive strains exhibited a higher maximum specific growth rate (µ max ) and a higher acidification rate than the proteinase-negative variants.The bacterial count and the lactic acid concentration after 15 h of incubation were also higher with the proteinase-positive strains.The acidification rate and the lactic acid concentration after 15 h of incubation for all lactococci were significantly higher in reconstituted goat milk than in cow milk and increased with the total solid contents in reconstituted milk.The µ max and the viable counts obtained after 15 h of incubation for lactococci were relatively close in reconstituted goat and cow milks, with the exception of the Wg2S and Wg2L strains.For these strains, the µ max values were significantly higher in goat milk, but their bacterial counts after 15 h of incubation were lower in goat milk.An uncoupling was observed for these strains in goat milk.In general, reconstituted goat milk was an appropriate medium for the production of mesophilic lactic starters.However, to prevent an uncoupling with some strains such as the Wg2S and Wg2L strains, incubation in reconstituted goat milk at 21 °C should be shorter than incubation in reconstituted cow milk.
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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) | 0.000 | 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 | 0.001 |
| 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".