The evaluation of mixtures of yeast and potato extracts in growth media for biomass production of lactic cultures
Bibliographic record
Abstract
The effectiveness of yeast extracts (YE) and potato extracts (PE) to promote growth of seven lactic cultures was evaluated by automated spectrophotometry (AS). Two aspects of the growth curve were analysed: (1) maximum biomass obtained (using ODmax) and (2) highest specific growth rate mu(max)) Eleven lots from the same PE-manufacturing process were examined for lot-to-lot variability. The ODmax values of three of the seven strains were significantly affected by lot source, but mu(max) was not significantly affected. The growth of bacteria was systematically lower in base medium containing 100% PE than in base medium containing 100% YE for both ODmax or mu(max) data, which could be related to the lower content in nitrogen-based compounds in PE. In AS assays, highest OD values for Lactobacillus casei EQ28, Lactobacillus rhamnosus R-011, Lactobacillus plantarum EQ12, and Streptococcus thermophilus R-083 were obtained with a mixture of PE and YE. Fermentations (2 L) were also carried out to determine the accuracy of AS to predict biomass levels obtained under fermentation trials. In these fermentations, replacement of 50% YE with PE was shown to enable good growth of S. thermophilus. With L. rhamnosus R-011, a high correlation (R2 = 0.95) was found between ODmax data obtained in the AS assays and that of the 2-L bioreactor when the same growth medium was used for both series of fermentations. However, AS was not as efficient when industrial media were used for the bioreactor assays. The relationship was still good for ODmax between AS data and that of the bioreactor data with L. rhamnosus R-011 in industrial LBS medium (R2 = 0.87), but was very poor with the S. thermophilus R-083 on Rosell #43 industrial medium (R2 = 0.33). Since PE cost 40% less than YE, there are strong economic advantages in considering such a partial replacement of YE by PE.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".