The effect of probiotics as a starter culture for producing yogurt
Bibliographic record
Abstract
Background: Many comprising studies showed that probiotics can manifest antimicrobial activity. Due to positive health effects of probiotics, they have been added in a fermentation of various foods to increase the nutrient content and to improve the quality of the foods. Furthermore, probiotics are used as a starter culture for several fermented foods like a yogurt. Probiotics may contain strains that are capable of initiating fermentation of the foods, however, a safety of the foods is not certain. Therefore, the study is done to analyze use of probiotics as a starter culture for a yogurt. Methods: The study was designed to analyze the pH pattern of three different yogurt groups (control, commercial starter culture, and probiotics). Each group had three samples that were made using Dairyland 2% milk and corresponding cultures. The control group samples were not inoculated with any culture. The commercial starter culture group samples were inoculated with Yogourtmet Freeze-Dried Starter and the probiotics group samples were inoculated with probiotic capsule, Jamieson 10 Billion Probiotic. The samples were incubated for 7 hours and every 45 minutes the pH was measured using Hanna Professional Portable Yogurt pH Meter. Results: The statistical analysis of the pH measurement showed significant different between the control groups and other two groups. The control group samples pH decreased a bit, but it was not enough to turn the samples to a yogurt. The pH pattern of the commercial group samples showed rapid decrease in pH after 180 minutes and the average pH of the last reading was 4.10. The pH of the probiotics group samples decreased linearly, and the average pH of the last reading was 4.58. Conclusions: The commercial starter culture and the probiotics group samples initiated fermentation and enough acidification occurred to decrease the pH below 4.6. With 7 hours of incubation period, the probiotics group samples just met the pH that makes the yogurt safe to consume. Therefore, the use of the probiotics as a starter culture for producing yogurt can be suggested with adequate incubation period.
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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 | 0.000 |
| 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 | 0.000 |
| 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".