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Record W4399580135 · doi:10.3390/applbiosci3020018

Sustainable Pulse Proteins: Physical, Chemical and Fermentative Modifications

2024· article· en· W4399580135 on OpenAlexaff
S. Ganeshan, Nancy D. Asen, Yingxin Wang, Mehmet Tülbek, Michael T. Nickerson

Bibliographic record

VenueApplied Biosciences · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMeat and Animal Product Quality
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsMouthfeelBiotechnologyBiochemical engineeringFermentationFood scienceBusinessBiologyRaw materialEngineering

Abstract

fetched live from OpenAlex

Pulse proteins are playing significant roles in the alternative protein space due to the demand for foods produced in an environmentally sustainable manner and, most importantly, due to the demand for foods of nutritious value. There has been extensive research to mimic animal-derived meat texture, flavour, mouthfeel, etc. However, there is still the perception that many of the plant-based proteins that have been texturized to mimic meat are still highly processed and contain chemicals or preservatives, reducing their appeal as being healthy and precluding any sustainable benefits. To counter this notion, the biotransformation of pulse proteins using enzymes or fermentation offers unique opportunities. Thus, this review will address the significance of pulse proteins in the alternative protein space and some of the processing aids leading to the isolation and modification of such protein concentrates in a sustainable manner. Fermentation-based valorization of pulse proteins will also be discussed as a “clean label” strategy (further adding to sustainable nutritious plant protein production), although some of the processes like the extensive use of water in submerged fermentation need to be addressed.

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 score0.099
Threshold uncertainty score0.253

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 head0.031
GPT teacher head0.270
Teacher spread0.239 · 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

Citations8
Published2024
Admission routes1
Has abstractyes

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