Protein quality of a probiotic beverage enriched with pea and rice protein
Bibliographic record
Abstract
The aim of this study was to evaluate the effect of the fermentation of a probiotic beverage enriched with pea and rice proteins (PRF) on its protein quality. The protein quality was determined as the protein efficiency ratio (PER), net protein ratio (NPR), and the apparent (AD) and the true digestibility (TD) evaluated in vivo. The probiotic beverage was incorporated to a rat diet at a final concentration of 10% protein, for the evaluation of the PER, the NPR, the AD, and the TD. The protein digestibility amino acid score was also calculated. Results showed that the fermentation of beverage enriched with PRF had no effect on the TD but significantly increased the PER and the NPR (P ≤ 0.05) from 1.88 to 2.32 and from 1.66 to 2.30, respectively. Thus, the fermentation increased the protein quality of the PRF probiotic beverage. In addition, to determine if the beverage constitute in a good carrier matrix for the probiotics, the level of alive probiotics in the feces was evaluated and showed a concentration of 7.4 log CFU/g. PRACTICAL APPLICATION: Plant proteins are often of lower quality compared to animal proteins. Lactic acid fermentation of pea and rice protein has allowed to reach the same protein quality as casein. A plant-based fermented beverage with high protein quality and enriched with probiotics was developed.
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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) | 0.001 | 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".