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Record W2905923926 · doi:10.3168/jds.2018-15392

Estimation of correction factors to determine the true amino acid concentration of protein after a 24-hour hydrolysis

2018· article· en· W2905923926 on OpenAlexaff
H. Lapierre, Simon Binggeli, M. Sok, D. Pellerin, D.R. Ouellet

Bibliographic record

VenueJournal of Dairy Science · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRuminant Nutrition and Digestive Physiology
Canadian institutionsUniversité LavalAgriculture and Agri-Food Canada
Fundersnot available
KeywordsRumenCanolaSilageHydrolysisSoybean mealFood scienceChemistryComposition (language)MealAnimal scienceChromatographyBiologyBiochemistryFermentationOrganic chemistry

Abstract

fetched live from OpenAlex

Although it has been acknowledged for a long time that a single period of hydrolysis, normally 21 to 24 h, is not the optimal time for most of the AA, a single period is routinely used due to time and cost constraints. As models to balance dairy rations for proteins are evolving toward balancing for AA, it becomes critical to improve the predictions of AA supply from digested proteins. Our objective was to develop correction factors that could systematically be applied to AA concentrations obtained after a 24-h hydrolysis of proteins to account for incomplete recovery and therefore determine their true AA composition. Thirteen substrates were selected to represent different types of proteins commonly used to estimate the supply of AA in ration formulation models: feed ingredients (grass silage, corn silage, soybean meal, canola meal, high-protein corn dried distillers grains, and wheat dried distillers grains plus solubles), 16-h rumen residues (soybean meal and canola meal), digesta (duodenal digesta and feces), and rumen microorganisms (fluid-associated bacteria, particle-associated bacteria and protozoa). Each protein was hydrolyzed in 6 N HCl for multiple hydrolysis times: 13 (2, 4, 8, 12, 18, 21, 24, 30, 48, 72, 96, 120, and 168 h) for feed ingredients, rumen residues, and digesta, and 9 (2, 4, 8, 18, 24, 30, 48, 96, and 168 h) for rumen microorganisms; all analyses were conducted in triplicate. Using nonlinear regression, the AA composition in the protein before the hydrolysis (A 0 ) was derived for each AA in each protein. Two ratios were calculated as potential correction factors: A 0 /24-h concentration (A 0 /24h) and the maximal concentration/24-h concentration (max/24h). Both ratios were tested to determine if the type of proteins was affecting them. The ratios A 0 /24h were not affected by the type of proteins, whereas the ratios max/24h were also not affected by the type of proteins except for 3 nonessential AA (Ala, Glu, and Gly). In an attempt to propose correction factors, our results were combined with results from the literature reporting ratios A 0 /24h, ratios max/24h, or the ratio of the AA composition calculated from gene structure/24 h. The correction factors proposed for individual AA varied from 1.02 (Asp) to 1.12 (Thr). For the essential AA, the highest ratios were obtained, as expected, for the branched-chain AA and Thr. Formulation programs balancing dairy rations for essential AA would need to acknowledge the incomplete recovery of AA when obtained from 24-h hydrolysis and include correction factors, specific for each AA, but the same across different types of proteins, to correctly estimate the true AA supply to dairy cows.

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)0.003
metaresearch head score (Gemma)0.010
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: Methods · Consensus signal: Methods
Teacher disagreement score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.020
GPT teacher head0.246
Teacher spread0.226 · 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
GenreMethods

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

Citations23
Published2018
Admission routes1
Has abstractyes

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