Yacon Prebiotic Functional Beverages, the Sensory, Antioxidant Profiles, and Shelf Stability
Bibliographic record
Abstract
The increasing awareness on overall health of consumers has driven a shift from fruit juices and carbonated beverages to functional beverages. This research aimed to incorporate yacon concentrate to the formulation of functional beverages to improve the health-related properties. Using yacon concentrate as main ingredients, three functional prototypes have been developed: yacon-collagen, yacon-blackcurrant, and yacon-vitamin c. Sensory evaluation for yacon-collagen and yacon-blackcurrant beverages was conducted by a 9-point hedonic scale. Antioxidant activities of three yacon beverages were evaluated using the CUPRAC, DPPH, and FRAP assays. Yacon-collagen and yacon-blackcurrant beverages were sensory acceptable with ratings above the centre point of the scores (all ratings > 5, n = 50) on four sensory attributes (appearance, sweetness, flavor, overall liking). The antioxidant capacity of yacon-collagen, yacon-blackcurrant, yacon-vitamin c, and yacon concentrate were 1941mg/2300mg/1891mg/1193mg TE/100g (CUPRAC), 1943mg/2404mg/2122mg/1365mg TE/100g (DPPH), and 1219mg/2614mg/2990mg/992mg TE/100g (FRAP). The antioxidant capacity of yacon-blackcurrant and yacon-vitamin c were much higher than that of yacon concentrate because blackcurrant and vitamin c enhanced the antioxidant capacity. The development of yacon functional beverages with acceptable taste, verified health-related properties, applicable shelf-life, as new dietotherapy applications of yacon concentrate, could provide more healthier food products for consumers to exercise healthier food choices.
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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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".