Physicochemical and Functional Properties of Protein Isolates Obtained from Several Pea Cultivars
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 it