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Record W4402533319 · doi:10.1093/jas/skae234.248

57 In vitro degradation kinetics of protein and starch from equine feedstuffs (corn, beet pulp, oat hulls, soybean meal, whey, timothy, and alfalfa hay)

2024· article· en· W4402533319 on OpenAlexaff
Cara Cargo-Froom, Matthew G. Nosworthy, Priska Darani, Sharifa Darani, Scott Cieslar, J.L. Ellis

Bibliographic record

VenueJournal of Animal Science · 2024
Typearticle
Languageen
FieldNursing
TopicFood composition and properties
Canadian institutionsAgriculture and Agri-Food CanadaUniversity of Guelph
Fundersnot available
KeywordsHayBeet pulpSoybean mealStarchMealAgronomyFood sciencePulp (tooth)ChemistryBiologyRaw materialMedicine

Abstract

fetched live from OpenAlex

Abstract Meaningful progress can be made in the field of equine nutrition through improved feed characterization and the development of in vitro nutritional models to describe nutrient degradation. The objective of this study was to assess at which time point macronutrient degradation reached plateau when equine feedstuffs were digested using a static two-step enzymatic digest. Prior to addition of any enzymes, 10 g of each ingredient was weighed in triplicate into digestion vessels and hydrated with 50 mL water. To initiate gastric digestion, 60 mL of 0.1M hydrochloric acid-pepsin solution (pH 2) was added to the digestion vessels and incubated for 2 h at 39℃ under constant mixing. The liquid fractions of the digestions were sampled at 0, 5, 10, 20, 30 60, 90 and 120 min. Post-gastric digestion, samples were neutralized with 1 M sodium hydroxide and raised to a pH of 6.8. To initiate small intestinal digestion, 42 mL of a pancreatin-phosphate buffer (pH of 6.8) was added to the digestion vessels and incubated for 18 h at 39℃ under constant mixing. The liquid fractions of the digestions were sampled at 0, 5, 10, 20, 30 60, 90, 120, 150, 180 min and thereafter hourly up until the end of digestion (1,020 min). Liquid samples were analyzed for glucose via GOPOD kit to determine starch degradation and crude protein via combustion (LECO) and o-phthalaldehyde assay to determine protein degradation. A modified Chapmans-Richard (first order kinetics) model was fit to the time point data to determine the immediately soluble fraction, the degradable fraction, the degradation rate (Kd) of the degradable fraction, and the undegradable fraction (from the plateau point) of each ingredient. The rate and plateau were estimated for each ingredient by nonlinear regression procedures, that included a boundary of ≤ 100% for the plateaus (Table 1). Corn did not reach a plateau for glucose released; as such, the kinetic model could not be fit to the data points. The ingredients with the greatest and least rates of starch degradation were alfalfa hay (5.36 %/min) and oat hulls (0.11 %/min), respectively. The ingredients with the greatest and least rates of protein degradation were oat hulls (0.379 %/min) and whey (0.004 %/min), respectively. These preliminary results will be used to adjust the in vitro protocol used herein, as it is part of a larger project aiming to characterize the degradation of a wider collection of equine feedstuffs, with these degradation parameter profiles being used as inputs to a mechanistic digestion model. This combination of in vitro techniques and modelling will be advantageous in optimizing equine nutrition.

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 score0.002
Threshold uncertainty score0.004

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)0.0010.000

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 head0.032
GPT teacher head0.278
Teacher spread0.246 · 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

Citations2
Published2024
Admission routes1
Has abstractyes

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