MétaCan
Menu
Back to cohort

Determination of the in vivo and in vitro protein quality of pulse protein concentrates and isolates.

2016· article· en· W3173574345 on OpenAlexaffabout
Matthew G. Nosworthy, Jason Neufeld, James D. House

Bibliographic record

VenueThe FASEB Journal · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicProteins in Food Systems
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsProtein qualityProtein digestibilityCaseinIn vivoProtein efficiency ratioDigestion (alchemy)Food scienceIn vitroBioassayPea proteinBiologyLimitingTryptophanAmino acidSoy proteinChemistryBiochemistryBiotechnologyChromatographyWeight gainBody weight

Abstract

fetched live from OpenAlex

Currently, the use of a rodent bioassay is the officially recognized method for generating data in support of protein content claims for food ingredients. Although there are in vitro methods for calculating protein digestibility, to date no method has been accepted by North American regulatory agencies for use in establishing protein content claims, likely due to a lack of evidence in support of their validity. To this end, we compared the in vivo (%True Fecal Protein Digestibility; %TFPD) and the in vitro protein digestibility (%IVPD) of faba bean, lentil and pea protein concentrates and isolates. Sprague‐Dawley rats (n=70, ~70 g) were randomized to one of seven diets (10% crude protein) based on: casein (reference control), the concentrates of faba bean (FB60), lentil (L55) or pea (P55) or the protein isolates of the same pulses (FB85, L85 and P85 respectively). The %TFPD and protein digestibility corrected amino acid score (PDCAAS) were calculated. The %IVPD was determined via enzymatic digestion with subsequent pH drop, and used to calculate the in vitro PDCAAS (IVPDCAAS). Except for L55, in which the sulfur amino acids were limiting, all experimental diets were limited by tryptophan content. FB60 had a higher AAS than FB85 (0.46 vs 0.58) whereas the AAS of the other diets had the opposite trend (L55‐0.75 vs L85‐ 0.52, P55 – 0.58 vs P85‐ 0.54). Digestibility was greater in the protein isolates than the concentrates, and the in vivo rat bioassay reported higher digestibility than the in vitro method; casein (95 vs 84), FB60 (94 vs 74), FB85 (97 vs 75), L55 (91 vs 75), L85 (96 vs 77), P55 (93 vs 78), P85 (97 vs 78). There was no correlation found between %TPD and %IVPD (R 2 = 0.027). Interestingly, a strong correlation was found between PDCAAS and IVPDCAAS (R 2 =0.99, p<0.0001), however the values from the rodent model were greater than the in vitro casein (89 vs 79), FB60 (43 vs 33), FB85 (56 vs 44), L55 (68 vs 56), L85 (50 vs 40), P55 (54 vs 46), P85 (53 vs 43). Excepting faba bean, all pulse concentrates had higher AAS, lower digestibility and greater PDCAAS values than their isolate counterparts. As such, processes used in the isolation of pulse protein sources increased digestibility, but may have led to shifts in protein composition, leading to a lower PDCAAS value. Although the strong correlation found between PDCAAS and IVPDCAAS suggests that in vitro analysis could reduce the requirement of animal experimentation for protein claims, a larger dataset combined with investigation into other potential in vitro methods is required. Support or Funding Information Pulse Canada

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)0.001
metaresearch head score (Gemma)0.001
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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.028
GPT teacher head0.248
Teacher spread0.219 · 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

Citations5
Published2016
Admission routes2
Has abstractyes

Explore more

Same venueThe FASEB JournalSame topicProteins in Food SystemsFrench-language works237,207