Effects of Tea (Camellia sinensis) Phytochemicals on the Yoghurt Cultures (Lactobacillus bulgaricus and Streptococcus thermophilus) During Development and Storage of Tea Fortified Yoghurts
Bibliographic record
Abstract
Tea phytochemicals have been reported to exhibit potent antimicrobial activity. This current study reports the ability of Streptococcus thermophilus and Lactobacillus bulgaricus to grow, survive and multiply in the presence of tea phytochemicals during development and storage of tea fortified yoghurts. Two Kenyan tea varieties clone TRFK 6/8 (standard black quality tea) and clone TRFK 306/1 (newly developed purple leafed tea clone), were processed as aerated and non-aerated teas and used to develop tea fortified yoghurt. The teas were added at concentrations of 0, 1, 2 and 4 g in 250 mL volumes of milk (w/v) which was predetermined by sensory tests. The results showed that tea phytochemicals at the added ranges had no adverse effect on the growth of Lactobacillus bulgaricus and Streptococcus thermophilus; however, yoghurt setting time was prolonged at a mean time of 4.11, 5.22, 7.29 and 8.26 hrs respectively for tea concentrations of 0, 1, 2 and 4 g/250 mL milk. The mean microbial load for Lactobacillus bulgaricus and Streptococcus thermophilus in black, green and purple tea yoghurts were also inversely proportional to the concentration of the added teas. In the developmental stages of tea fortified yoghurts Lactobacillus bulgaricus range was 0.52-1.58 × 107 CFU/mL while Streptococcus thermophilus range was 2.53-3.51 × 109 CFU/mL, during storage the growth patterns were different between the cultures. The recorded mean values range for Lactobacillus bulgaricus was 2.79-4.35 × 107 CFU/mL while Streptococcus thermophilus mean range was 2.57-3.47 × 109 CFU/mL Phytochemicals traced in the product had concentration values below 5 × 102 µgmL-1. In conclusion, it was possible to develop probiotic tea fortified yoghurt containing tea phytochemicals with unlimited health benefits using different the different tea clones.
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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".