Pea and lentil flour quality as affected by roller milling configuration
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract This study examined the effects of roller mill configuration on pulse flour quality. Dehulled yellow pea and green lentil were ground to flour using a laboratory roller mill characterized by its flexibility to control particle size reduction while maintaining a constant feed rate. The milling diagram length (long, six passes vs. short, four passes) and sieve sizes (large, 300 μm vs. tight, 180/150 μm) were adjusted for a total of four milling configurations. Each flour stream was characterized with respect to its physical properties and chemical composition. No notable differences were identified between pea and lentil based on how the milling configuration influenced flour characteristics. Overall, combining streams to produce a whole flour did not affect the chemical composition but resulted in variability for physical characteristics as indicated by a tendency toward increased levels of damaged starch with the shorter milling diagram. Damaged starch content was found to be indirectly associated ( p < 0.05) with the particle size distribution, where the highest concentrations were noted in flours with median distributions below 30 μm. When individual streams were compared across milling configurations, the stream itself was rarely found to significantly influence flour physicochemical properties. However, the variation exhibited in particle‐size distribution, protein, starch, ash, and damaged starch content could have practical relevance given the many significant ( p < 0.05) correlations with functional properties that could subsequently affect the end‐use applicability of flours. This would imply that specialized flours could be made with the intention of being used for defined food applications.
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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 | 0.000 | 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 it