Physicochemical and Functional Properties of Protein Isolates Obtained from Several Pea Cultivars
Bibliographic record
Abstract
The goal of this research was to investigate the physicochemical and functional properties of protein isolates obtained from several pea cultivars grown at two locations in Canada. The functionalities of the pea protein isolates (PPIs) were then compared with those of commercial food protein ingredients derived from milk, egg, pea, soy, and wheat. Six pea cultivars (Agassiz, CDC Golden, CDC Dakota, CDC Striker, CDC Tetris, and Cooper) were collected from two years over two locations in Saskatchewan (Canada). Samples were evaluated for composition, surface properties, and functional properties. All PPIs had protein levels of ≈91% (db) and isolate and protein yields of ≈18 and ≈72%, respectively. Cultivars exhibited legumin/vicilin ratios from 0.36 (Agassiz) to 0.79 (CDC Golden). Differences among cultivars as well as significant cultivar × environment interactions were found only for maximum intrinsic fluorescence (195–267 arbitrary units), solubility (63–75%), and foaming capacity (167–244%). No differences owing to either cultivar or environment were observed for surface charge (zeta potential = approximately –24 mV), oil holding capacity (≈3.2 g/g), foam stability (≈75%), or emulsion stability (≈96%). Relative to the commercial isolates, PPIs prepared under laboratory conditions behaved most similarly to soy isolates, with the exception of solubility. Whey and egg were superior in solubility and foaming properties, whereas wheat and the commercial pea protein product were significantly lower in nearly all of the functionality tests. Based on their oil holding properties, the laboratory‐prepared PPIs may serve as good meat extenders. The findings also suggest that pea processors may not need to specify either the cultivar or the environment when acquiring raw material, thus creating advantages in their feedstock sourcing.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 source (direct Gemma or distilled Codex), 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".