Effect of Genotype on the Properties of Flours and Protein Isolates Derived From Wrinkled and Round Peas
Bibliographic record
Abstract
ABSTRACT Background and Objectives This study evaluated the effect of seed shape on the composition, functional, and quality properties of pea flours and protein isolates. Wrinkled‐seed (WPAs) and round‐seed (RPA) pea accessions were selected from a genome‐wide association study panel. Findings Flours from WPAs exhibited 27.4% protein and 33% starch content, whereas RPA presented 22.2% and 45.8%, respectively. These differences reflected the genetic background of the rugosus mutation in WPAs. Conversely, RPA protein isolates showed higher protein (91.8%) compared with WPAs (87.9%). Seed shape did not have a significant effect on the emulsifying and foaming properties of pea flours (EAI = 13 m 2 /g; FC = 277%) and protein isolates (EAI = 20.8 m 2 /g; FC = 184.1%); therefore, no trend could be delineated in terms of shape × functionality. Overall, RPA had higher in vitro protein digestibility (IVPD) in both flours and isolates compared to WPAs, but amino acid scores did not differ significantly between RPA and WPAs. Conclusions Seed shape impacted the proximate composition and quality of pea flours and protein isolates, whereas functionality did not differ significantly between WPAs versus RPA. Significance and Novelty Our findings highlight the variability in pea composition and nutritional quality driven by genetic factors associated with seed shape, with opportunities for selecting genotypes and processing methods to optimize nutritional and functional attributes in pea products.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".