The Assessment of In Vitro Protein Digestibility and Quality on Mechanically Scoured and Moisture Conditioned Navy Beans (<i>Phaseolus vulgaris</i>) and Chickpeas (<i>Cicer arietinum</i>) Subject to Roller‐Milling
Bibliographic record
Abstract
ABSTRACT Background and Objectives Roller‐milling practices for pulses to establish potential end‐use applications are required. Scouring and moisture conditioning may improve milling efficiency and hull removal, in addition to influencing nutritional quality. In this study, the extent of these conditions on the protein digestibility and quality are evaluated in vitro on navy beans and chickpeas. Findings Scouring with no additional moisture conditioning increased protein quality in both navy beans and chickpeas, whereas the addition of 1% moisture conditioning in combination with scouring was detrimental to protein quality. Moisture conditioning at 0.5% without scouring also decreased protein quality in navy beans. Changes in protein quality were primarily due to compositional changes in both protein and amino acid content, reflected in amino acid scoring. Sulfur amino acids were the sole limiting amino acids in navy beans, while tryptophan was the sole limiting amino acid in chickpeas, irrespective of the roller‐milled flour stream or Pretreatment. Conclusion Scouring with no added moisture conditioning effectively improves the protein quality in both navy beans and Kabuli chickpeas due to changes in their amino acid scoring pattern. Significance and Novelty Balancing milling practices and nutritional quality is important in developing navy bean and Kabuli chickpea products.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".