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Record W3035069738 · doi:10.1080/10942912.2020.1772285

Comparative study of the structural and functional properties of protein isolates prepared from edible vegetable leaves

2020· article· en· W3035069738 on OpenAlexafffund
A.A. Famuwagun, Adeola M. Alashi, Saka O. Gbadamosi, Kehinde A. Taiwo, Durodoluwa Joseph Oyedele, O.C. Adebooye, Rotimi E. Aluko

Bibliographic record

VenueInternational Journal of Food Properties · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicProteins in Food Systems
Canadian institutionsUniversity of Manitoba
FundersGlobal Affairs CanadaInternational Development Research Centre
KeywordsIsoelectric pointAmaranthChemistryFood scienceProtein isolateSurface proteinIsoelectric focusingBiochemistryBiologyEnzyme

Abstract

fetched live from OpenAlex

Isoelectric precipitation was used to produce protein isolates (>90% protein contents) from three edible vegetable leaves. Amaranth (ALI), eggplant (ELI) and fluted pumpkin (FLI) leaf protein were isolated to study their conformational structures. Intrinsic fluorescence indicated a loose structural conformation for ELI at all the pH values, whereas FLI and ALI had more compact structures at pH 3.0 and pH 9.0. The surface hydrophobicity showed a greater distribution of hydrophobic amino acid groups of the protein isolates at the basic than the acidic regions. The SDS-PAGE results showed that the leaf isolates had similar polypeptide bonds characterized by 20, 25, 40 and 200 kDa and some distinct bands above 200 kDa. The ELI formed emulsions with significantly (p < .05) smallest oil droplet sizes (<3.3 µm) when compared to FLI and ALI. However, foaming capacity was mostly pH-dependent with significantly (p < .05) higher values at pH 7.0 and 9.0. The leaf protein isolates may be considered as potential functional food ingredients.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.001

Distilled classifier scores by category (both heads)

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 head0.091
GPT teacher head0.234
Teacher spread0.143 · 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 source (direct Gemma or distilled Codex), 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

Citations43
Published2020
Admission routes2
Has abstractyes

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