MétaCan
Menu
Back to cohort

Amino acid profile, protein digestibility, thermal and functional properties of Conophor nut (<i>Tetracarpidium conophorum</i>) defatted flour, protein concentrate and isolates

2012· article· en· W1873636426 on OpenAlexaff
Saka O. Gbadamosi, Sumbo H. Abiose, Rotimi E. Aluko

Bibliographic record

VenueInternational Journal of Food Science & Technology · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicProteins in Food Systems
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsIsoelectric pointChemistryAmino acidFood scienceAspartic acidEmulsionThermal stabilityChromatographyProtein qualityLysineBiochemistryEnzymeOrganic chemistry

Abstract

fetched live from OpenAlex

Summary Functional properties, amino acid compositions, in vitro protein digestibility, electrophoretic and thermal characteristics of conophor defatted flour (CDF), conophor protein concentrate (CPC), isoelectric protein isolate (CII) and neutral protein isolate (CNI) were evaluated. The isolates (CII and CNI) showed significantly lower ( P &lt; 0.05) water and oil absorption capacities, emulsifying and gelling capacities, but higher emulsion stability and foaming capacity. In vitro protein digestibility, enthalpy and denaturation temperature varied between 52.28% and 73.4%, 1.62–4.04 J g −1 protein and 79.7–89.3 °C, respectively. The native proteins were comprised of subunits with molecular weights ranging between 15.3 and 129.3 kDa. The major amino acids in all the samples were aspartic acid, glutamic acid and arginine, whereas the percentages of essential amino acids in CDF, CPC, CII and CNI were 39.35%, 40.46%, 44.54% and 46.04%, respectively. Conophor protein products could be used as functional ingredients in food formulations and for enriching low quality protein diets.

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)0.001
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 score0.007
Threshold uncertainty score0.671

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.025
GPT teacher head0.224
Teacher spread0.199 · 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

Citations51
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Food Science & TechnologySame topicProteins in Food SystemsFrench-language works237,207