Production of lactic acid by Lactobacillus acidophilus LA5 and Bifidobacterium lactis BB12 in batch fermentation of cheese whey and milk permeate
Bibliographic record
Abstract
Lactic acid (2-hydroxyproponic acid) is an important organic acid with widespread applications in the food, pharmaceutical, detergent and agricultural industries. For this purpose, the effects of nutrients and important environmental factors on the production of lactic acid using the by-product of dairy plants (cheese whey and milk permeate) as a culture medium with pure culture of Lactobacillus acidophilus LA5 and Bifidobacterium animalis subsp. lactis BB12 were investigated. The results of statistical analysis of the data showed a significant effect of initial pH, incubation temperature, yeast extract concentration, type of culture medium and type of bacteria on lactic acid production (p <0.05). The incubation time, type of probiotic bacteria and yeast extract concentrations had a significant effect on cell density (p < 0.05). As well, the effect of initial pH, temperature and incubation time, yeast extract concentration, culture medium and probiotic bacteria on pH were significant (p < 0.05). Although the results of this study showed that milk permeate and cheese whey due to their high content of lactose can be a suitable medium for the production of lactic acid, the cost of using supplements, especially the nitrogen source, is essential.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".