Glycemic Responses and Sensory Characteristics of Whole Yellow Pea Flour Added to Novel Functional Foods
Bibliographic record
Abstract
A fundamental understanding regarding postprandial glycemic responses to foods containing whole yellow-pea flour (WYPF) remains unknown. This, alongside concerns that WYPF possesses unfavorable sensory characteristics has limited the incorporation of WYPF into new functional food products as a healthy novel ingredient. The objective of this study was to evaluate how WYPF modulates postprandial glycemic responses as well as sensory characteristics in novel foods. In a single-blind crossover trial, the present study assessed postprandial glycemic responses of banana bread, biscotti, and spaghetti containing either WYPF or whole wheat flour (WWF). Boiled yellow peas (BYP) and white bread (WB) were used as positive and negative controls, respectively. On day 1, subjects evaluated appearance, taste, texture, smell as well as overall acceptance of each WYPF and WWF food on a 5-point hedonic scale. WYPF banana bread (97.9 +/- 17.8 mmol x min/L) and biscotti (83 +/- 13 mmol x min/L), as well as BYP (112.3 +/- 19.9 mmol x min/L), reduced (P < 0.05) glycemic responses compared to WB (218.1 +/- 29.5 mmol x min/L). The glycemic response of WYPF pasta (160.7 +/- 19.4 mmol x min/L) was comparable to WB. WYPF biscotti produced a lower (P = 0.019) postprandial glycemic response compared to WWF biscotti (117.2 +/- 13.1 mmol x min/L). Hedonic responses between corresponding foods were similar except for the WYPF pasta (2.9 +/- 0.9) which possessed a lower sensory score (P = 0.02) for smell compared to WWF pasta (3.6 +/- 1). WYPF can be used to produce low-glycemic functional foods possessing sensory attributes that are comparable to identical food products containing WWF.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".