Growth‐promoting properties of yeast extracts produced at different pH values, with different autolysis promoters and bacterial populations
Bibliographic record
Abstract
Abstract The effect of the autolysis conditions of bakers' yeast on the growth‐promoting properties of the resulting yeast extracts (YE) were examined on cultures of Lactococcus lactis ssp lactis D25 and of Lactococcus lactis ssp cremoris R2. The various YE were produced by conducting autolysis at four pH levels (pH 4.0, 5.5, 7.0 or 8.5) and with or without the autolysis promoters (AP) ethyl acetate or chitosan. To determine if the presence of contaminating bacteria during autolysis affected the YE characteristics, one series of YE was also prepared with the bakers' yeast cell suspension contaminated with 108 CFU/cm−3 of typical yeast plant bacteria (mostly of the Bacillus genus) at the beginning of autolysis. The growth curves of the lactococci in media supplemented with the various YE were analyzed to determine the maximum optical density (ODmax), the maximum growth rate (µmax) and the fermentation time (F‐time) at which ODmax was reached. The addition of bacterial contaminants (at 108 CFUcm−3) did not significantly influence the growth‐promoting properties of YE. The lactococci had higher ODmax and µmax values when the media contained YE produced at pH 4.0 or 5.5, and these YE contained 40% more total nitrogen than those obtained at pH 7.0 or 8.5. There was no major effect of AP on the biological value of the resulting YE, but a significant interaction between pH and AP was found for L lactis D25. Thus the ODmax of YE produced at pH 7.0 and 8.5 were highest when ethyl acetate was used as autolysis promoter, as compared with control and chitosan at pH 7.0–8.5, while the opposite was obtained with products produced at pH 4.0 and 5.5. This study shows that parameters used to produce YE influence their biological value with respect to the growth‐promoting properties of lactococci. © 2001 Society of Chemical Industry
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) | 0.001 | 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) | 0.001 | 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".