The Growth of Different Probiotic Microorganisms in Soymilk from Different Soybean Varieties and their Effects on Anti-oxidant Activity and Oligosaccharide Content
Bibliographic record
Abstract
Soymilk is a good source of proteins and health-promoting isoflavones, but it contains oligosaccharides that cause flatulence. Fermenting it with probiotic bacteria may reduce the oligosaccharides and enhance its health benefits.The present study determined the growth of different lactic acid bacteria (LAB) in soymilk obtained from soybean varieties grown in Rwanda and the effect of fermentation on oligosaccharides that cause flatulence (stachyose, raffinose and verbascose), and antioxidant activity of fermented soybean milk. After fermentation at 30°C for 24 hours, Lactobacillus plantarum, Lactobacillus acidophilus, Lactobacillus brevis, Lactobacillus reuteri, Lactobacillus rhamnosus, Lactococcus cremoris and Lactobacillus casei attained around 8 log CFU/ml, which is sufficient for probiotic effects. However, only L. reuteri, L. brevis and L. plantarum caused sufficient drop in pH and increase in viscosity characteristic of a good fermented product. Soymilk from different soybean varieties did not show significant differences in the growth of these three LAB.These LAB reduced content of oligosaccharides and total polyphenols, but increased antioxidant activity in soymilk, which translate into health benefits of fermented soybean products.
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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".