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Record W4401122429 · doi:10.3390/foods13152411

Nitrogen Gas-Assisted Extrusion for Improving the Physical Quality of Pea Protein-Enriched Corn Puffs with a Wide Range of Protein Contents

2024· article· en· W4401122429 on OpenAlexafffund
Siwen Luo, Jitendra Paliwal, Filiz Köksel

Bibliographic record

VenueFoods · 2024
Typearticle
Languageen
FieldNursing
TopicFood composition and properties
Canadian institutionsUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsExtrusionPea proteinNitrogenProtein qualityFood scienceEnvironmental scienceBiotechnologyChemistryAgronomyBiologyMaterials scienceMetallurgyOrganic chemistry

Abstract

fetched live from OpenAlex

Blowing agent-assisted extrusion cooking is a novel processing technique that can alter the expansion of extruded snacks and, thus, enhance their physical appeal, such as texture. However, to this day, this technique has only been studied for ingredients with limited protein contents (<30%). In this study, protein-enriched snacks were extruded using nitrogen gas as a blowing agent at a wide protein range (0–50%) to better explore the potential of this technique in manufacturing high-protein snacks. The results showed that, with nitrogen gas injection, extrudate radial expansion was significantly (p < 0.05) improved at 10% and 40% protein, while extrudate density was significantly reduced at 30% and 50% protein. Nitrogen gas-injected extrudates, especially at 50% protein, exhibited improvements in texture, including a reduction in hardness and an increase in crispness. Collectively, this study showed the promising potential of nitrogen gas-assisted extrusion in improving the physical appeal of innovative healthy snacks at a high protein level (i.e., 50%).

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 score0.025
Threshold uncertainty score0.383

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 head0.049
GPT teacher head0.295
Teacher spread0.245 · 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

Citations6
Published2024
Admission routes2
Has abstractyes

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