Physicochemical and Bitterness Properties of Enzymatic Pea Protein Hydrolysates
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Bibliographic record
Abstract
The effects of different proteolytic treatments on the physiochemical and bitterness properties of pea protein hydrolysates were investigated. A commercial pea protein isolate was digested using each of 5 different proteases to produce protein hydrolysates with varying properties. After 4 h of enzyme digestion, samples were clarified by centrifugation followed by desalting of the supernatant with a 1000 Da membrane; the retentates were then freeze-dried. Alcalase and Flavourzymetrade mark produced protein hydrolysates with significantly higher (P < 0.05) degree of hydrolysis when compared to the other proteases. Flavourzyme, papain, and alcalase produced hydrolysates that contained the highest levels of aromatic amino acids, while trypsin hydrolysate had the highest levels of lysine and arginine. Papain hydrolysate contained high molecular weight peptides (10 to 178 kDa) while hydrolysates from the other 4 proteases contained predominantly low molecular weight peptides (</= 23 kDa). DPPH (1,1-diphenyl-2-picrylhydrazyl) free radical scavenging activity of the Flavourzyme hydrolysate was significantly (P < 0.05) the highest while alcalase and trypsin hydrolysates were the lowest. Inhibition of angiotensin converting enzyme (ACE) activity was significantly higher (P < 0.05) for papain hydrolysate while Flavourzyme hydrolysate had the least inhibitory activity. Sensory analysis showed that the alcalase hydrolysate was the most bitter while papain and alpha-chymotrypsin hydrolysates were the least. Among the 5 enzymes used in this study, papain and alpha-chymotrypsin appear to be the most desirable for producing high quality pea protein hydrolysates because of the low bitterness scores combined with a high level of angiotensin converting enzyme inhibition and moderate free radical scavenging activity.
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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 | 0.001 | 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 | 0.001 |
| 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