Gelation and dough‐forming properties of canary seed protein concentrate in comparison with commercial soy protein concentrate and vital wheat gluten
Bibliographic record
Abstract
Abstract Background and Objectives In this study, a lab‐scale process was developed to aqueously de‐oil canary seed (yellow and brown‐seeded) flour and derive a protein concentrate. The protein concentrates prepared were evaluated for their gelation and bread dough‐forming properties. Findings The aqueous process successfully reduced the oil content in both yellow‐seed and brown‐seed roller‐milled flour. The protein concentrate prepared from yellow‐seed flour and brown‐seed flour had 74.9% and 68.6% purity (dry weight basis), respectively. Proteins showed high resistance to thermal denaturation (peak denaturation at 107°C). It was found that the least gelation concentration of both protein concentrates was 16% (w/w). There were no significant differences in viscoelastic properties and water holding capacity between the protein gels of these two canary seed types and the addition of salt did not noticeably improve these properties. Compared to canary seed, commercial soy protein showed better gelation properties. Both yellow and brown canary seed protein showed a good potential for improving bread dough strength when incorporated into a low‐gluten‐strength wheat flour and was comparable to commercial vital wheat gluten at 1%–3% (w/w) inclusion levels. Conclusions The new canary seed protein ingredients prepared by the solvent‐free aqueous‐based process hold good potential for application in food formulation based on their gelation and bread dough‐forming properties. Significance and Novelty The gelation and dough‐forming properties of canary seed were not previously studied; therefore, this study provides an insight into those properties for potential food applications for canary seed proteins, which is important for canary seed market diversification as a novel protein source.
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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 | 0.000 | 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 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".