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Record W4414793452 · doi:10.1002/cche.70011

Effect of Genotype on the Properties of Flours and Protein Isolates Derived From Wrinkled and Round Peas

2025· article· en· W4414793452 on OpenAlexafffund
Cassia Galves, Krishna Kishore Gali, Thomas D. Warkentin, James D. House, Michael T. Nickerson

Bibliographic record

VenueCereal Chemistry · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicProteins in Food Systems
Canadian institutionsUniversity of ManitobaUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of CanadaMinistry of Agriculture - Saskatchewan
KeywordsPea proteinStarchGenotypeProtein isolateComposition (language)Protein qualityWheat breadSignificant difference

Abstract

fetched live from OpenAlex

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.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.118

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.012
GPT teacher head0.197
Teacher spread0.185 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2025
Admission routes2
Has abstractyes

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