The improvement of the functional properties of a chickpea protein isolate through proteolysis with three proteases
Bibliographic record
Abstract
Abstract Background and objectives Enzymatic hydrolysis has previously been shown to have beneficial influences on the protein functionality of pulse protein isolates. To apply and optimize these benefits in chickpeas, a chickpea protein isolate (CPI) was hydrolyzed with three different proteases (trypsin, pepsin, and papain), to three different degrees of hydrolysis (DH): 5%, 10%, and 15%. Changes to zeta potential, hydrophobicity, water and oil holding capacity (WHC and OHC), as well as solubility, emulsifying, and foaming properties at pH 4.0, 7.0, and 10.0 of the various hydrolysates were then quantified and compared with one another in order to determine optimal hydrolytic conditions. Findings Increasing length of enzymatic treatments led to a gradual increase in zeta potential, and a rise in protein hydrophobicity. The solubility of trypsin and papain hydrolyzed CPI proteins increased at pH 10.0, while minor decreases in solubility were noted at pH 7.0. Increasing length of pepsin and papain treatment was noted to improve the water holding capacity (WHC), whereas hydrolysis with all three enzymes led to decreases in oil holding capacity (OHC). The emulsifying activity index (EAI) of the CPI increased following hydrolysis with all enzymes at pH 4.0 and 10.0, while at pH 7.0 no changes were observed. The emulsifying stability index (ESI) of the CPI increased following trypsin treatment at pH 4.0; at pH 10.0 emulsions appeared stable, exhibiting no separation over a 30‐min period. Foaming capacity (FC) increased following enzyme treatments at pH 4.0, pH 7.0, and more dramatically at pH 10.0. Foaming stability (FS) worsened at pH 10.0 following higher levels of trypsin hydrolysis (DH > 10%). Conclusions Approximately 15% hydrolysis with papain was shown as the best conditions to augment the emulsifying, foaming and water holding properties of a CPI material, potentially allowing for the generation of specialized chickpea protein ingredients. Significance and novelty A total of nine distinct CPI hydrolysates were generated and compared with one another to determine optimal hydrolytic conditions with respect to the functional properties of the CPI.
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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".