Influence of enzymatic hydrolysis, pH and storage temperature on the emulsifying properties of canola protein isolate and hydrolysates
Bibliographic record
Abstract
Summary The aim of this work was to enhance emulsification properties of canola proteins through enzymatic proteolysis and pH variaton. Canola protein isolate ( CPI ) and hydrolysates ( CPH s) were used to form emulsions at pH 4.0, 7.0 and 9.0 followed by storage at 4 or 25 °C for 7 days. Controlled enzymatic hydrolysis led to increased peptide bond cleavage with time (0.23 g/100 g in CPI to 7.18 g/100 g after 24‐h Alcalase hydrolysis). Generally, oil droplet sizes were smaller for emulsions made at pH 9.0, which suggest better quality than those made at pH 4.0 and 7.0. Trypsin hydrolysate emulsions were the most physically stable at pH 7.0 and 9.0; in contrast, the pepsin hydrolysate emulsions were unstable at all conditions. The results suggest that selective enzymatic hydrolysis could play an important role in enhancing successful incorporation of canola proteins and peptides into food systems as protein emulsifiers.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".