Investigation of the effect of bio-ap-irga dietary supplements on the composition and properties of yogurts
Bibliographic record
Abstract
Today, consumers pay special attention to the quality of their products. They also expect a high level of innovation. Thus, the dairy sector's supply is increasingly focusing on the use of various additives with proven health benefits. The modern market of functional products consists of 65% dairy products. The basis of the technology of functional food products is the modification of traditional products, which ensure an increase in the content of useful ingredients in them to a level correlated with the physiological norms of consumption. Many scientific studies from different regions of the world are engaged in research, and their goal is to identify herbal supplements that have a beneficial effect on the human body. A specific feature of plant raw materials is the ability to synthesize a large number of various chemical compounds of various natures that have physiological activity. This article presents the results of studies on the effect of a biologically active additive obtained by using whey protein concentrate, saskatoon berries and mountain ash. The results of the physico-chemical, organoleptic parameters of yogurt obtained using the developed dietary supplement are presented. It was found that the content of proteins, vitamin C, and polyphenols in the finished yoghurts significantly increased. An increase in antioxidant properties was noted. The data obtained indicate the biological value of the developed yogurt was enriched with BIO-AP-IRGA dietary supplement.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".