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Record W4415595792 · doi:10.1016/j.foodhyd.2025.112154

High moisture extrusion based texturization and functional modulation of pea protein isolate through integration with cultivated beef

2025· article· en· W4415595792 on OpenAlexaff
Vahid Baeghbali, Stephen R. Euston, Xi He, Manuela Donetti, Osama Maklad, Parag Acharya

Bibliographic record

VenueFood Hydrocolloids · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicProteins in Food Systems
Canadian institutionsUniversity of Toronto
FundersUK Research and InnovationHeriot-Watt UniversityUniversity of Kentucky
KeywordsChewinessPea proteinMicrostructureExtrusionTexture (cosmology)MoistureProtein isolateFlavour

Abstract

fetched live from OpenAlex

The increasing global demand for meat can be sustainably leveraged by alternative protein, but the inferior quality of current plant-based meat analogues has somewhat disillusioned consumers. Small inclusion level of cultivated beef (CB) to bulk pea protein isolate in the high moisture extrusion (HME) showed a process unlock how to modulate the texture and instrumental sensory properties of the hybrid pea protein extrudates. Such novel co-extrusion delivered improved physicochemical and flavour properties as well as imparted distinct change in texture and microstructure. A comparison between hybrid pea protein extrudates with 10% CB (E-PCB10) and 2% CB (E-PCB2) showed a clear enhancement of the water holding (∼16.7-fold) and oil holding (∼67-fold) capacities in E-CPB10 and the instrumental sensory analyses also showed up to 30% reduction of key off-flavour markers of pea protein in E-PCB10 along with reduction in bitterness and astringency. E-PCB10 and E-PCB2 exhibit different microstructure compared to E-PPI, and E-PCB10 showed increased hardness, resilience, cohesiveness and chewiness as well as the mechanical strength. The scanning electron microscopy of extrudates revealed that higher concentrations of cultivated beef disrupted the pea protein matrix and the laminar structure in E-PPI becomes less easy to discern in E-PCB2 and E-PCB10. The increasing percentage of CB leads to a more enhanced protein-protein cross-linking in E-PCB10. These findings demonstrated for the first time that an addition of as little as 2% and 10% of cultivated beef can modulate the texture and microstructure of pea protein extrudate. This could lead to a promising texturization process for plant protein via microstructure modulation, reducing off-taste, and enhancing functional features to develop high-quality, hybrid alternative protein-based meat analogue. A schematic overview of the design of experiment for high moisture extrusion process and the concomitant characterization tests applied to the resultant hybrid extrudates • Hybrid meat analogues via co-extrusion of pea protein and cultivated cells were produced • First application of high-moisture extrusion to hybrid plant–animal cell systems • Cultivated beef enhances texture, functionality, and sensory quality • Small cultivated beef additions improve properties significantly and reduce cost barriers

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 score0.307
Threshold uncertainty score0.285

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.013
GPT teacher head0.204
Teacher spread0.191 · 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

Citations3
Published2025
Admission routes1
Has abstractyes

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