Influence of coarse particles on nutritional quality of flour ingredients: A comparison between cereals and pulses
Bibliographic record
Abstract
Seeds of cereals (barley and oats) and pulses (pea and lentil) were milled into whole flours, followed by differential sieving to obtain coarse and fine streams. Percentages of coarse particles the portion well preserving the inherent matrix structure of seeds and comprising undivided starch, protein, and fiber of the three flour streams from the same crop followed a descending order of coarse > whole > fine. In vitro starch digestibility of the three streams of cooked cereal flours was comparable; by contrast, the contents of rapidly digestible starch (RDS, dry starch basis) of the cooked pea and lentil flours exhibited a consistent order of fine > whole > coarse, showing a negative correlation (r = -0.954, p < 0.01) with the percentages of coarse particles. The presence of more coarse particles had positive correlations with the contents of total dietary fiber of both cereal and pulse flours but was not well correlated with the in vitro protein digestibility corrected amino acid scores (IV-PDCAAS). Overall, the coarse pea and lentil flours were more nutritionally desirable because of their markedly higher contents of dietary fiber and phenolic compounds, lower starch digestibility, and greater IV-PDCAAS than the other flour streams. • %Total dietary fiber showed coarse > whole > fine in cereal and pulse flour streams. • In vitro starch digestibility of cooked pulse flours showed fine > whole > coarse. • %Coarse particles showed correlation with starch digestibility in pulse flours only. • Three flour streams from the same crop had similar in vitro protein digestibility. • Coarse pea and lentil flours were nutritionally more desirable than the other flours.
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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 | 0.001 |
| 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 | 0.001 | 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".