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Record W4414830936 · doi:10.1093/jas/skaf300.715

PSXIII-27 Effect of diet physically effective neutral detergent fiber and starch levels on ruminal fermentation of finishing beef cattle.

2025· article· en· W4414830936 on OpenAlexaff
Robson Dinardi, Thiago da Silva Santana, Janaiane Ferreira dos Santos, Gabriela Ribeiro, Anna Martins, Maria Santos, Gabriel O Ribeiro, M. C. Pereira

Bibliographic record

VenueJournal of Animal Science · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Nutrition and Health
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsSilageLatin squareNeutral Detergent FiberStarchDry matterFermentationFiberFactorial experiment

Abstract

fetched live from OpenAlex

Abstract This study aimed to evaluate the effect of diets containing different concentrations of physically effective neutral detergent fiber (peNDF) and starch on ruminal fermentation of finishing beef cattle. Eight ruminally cannulated Nellore steers (468.6±87.5 kg) were housed in individual pens (21 m²) and assigned to a replicated 4×4 Latin square design, balanced for carryover effects. The experiment followed a 2×2 factorial arrangement of treatments, with two peNDF levels (low: 8.5% of diet dry matter [DM] vs. high: 10.3% of diet DM) and two starch levels (22.5% vs. 45% of diet DM). Concentrate feedstuffs were ground through a 4-mm sieve before feeding, and all ingredients were accounted for in the peNDF calculation. Each experimental period lasted 21-d, consisting of a 14-d adaptation followed by a 7-d sampling phase. Corn silage was harvested from a single field, chopped to a theoretical chop length of 2.0 (low peNDF) or 9.0 mm (high peNDF), and included at 20% of DM in all diets. Additionally, diets contained finely ground corn grain, soybean hulls, soybean meal, citrus pulp, minerals, urea, and sodium monensin. Mean, minimum, duration, and area pH < 5.5 were not affected by peNDF, or interaction (P≥0.47). There were no peNDF or interaction effects (P≥0.47) for mean and ruminal minimum pH, and duration and area of ruminal pH < 5.5. Cattle-fed high starch diets had lower mean (high: 5.5 vs. low: 5.7; P< 0.01) and minimum ruminal pH (high: 4.9 vs. low: 5.4; P<0.05), and greater duration (high: 792.7 vs. low: 328.9 min/d; P< 0.01) and area of pH < 5.5 (high: 317.4 vs. low: 78.7 pH×min; P< 0.01). Cattle-fed low peNDF and low starch, and high peNDF and high starch had lower (interaction; P=0.02) maximum pH, with those fed high peNDF and low starch being intermediate but not different from cattle-fed low peNDF and high starch. There were no peNDF or peNDF×starch interaction effects (P≥0.47) for molar proportions of ruminal acetate, propionate, and butyrate, and ruminal ammonia concentration. Total short-chain fatty acids concentration tended (P=0.08) to be greater for cattle-fed low peNDF and low starch. Feeding high starch decreased the molar proportion of acetate (high: 64.1 vs. low: 68.9 mol/100 mol; P< 0.01) while increasing the molar proportion of propionate (high: 21.0 vs. low: 17.6 mol/100 mol; P=0.04) and ruminal ammonia concentration (high: 9.7 vs. low: 5.7 mg/dL; P< 0.01). Altering the theoretical chop length, a practical approach to manipulating peNDF while maintaining the same dietary NDF from roughage did not affect the ruminal fermentation. However, increasing starch levels in finishing diets affected ruminal fermentation. The present data suggest that starch level has a greater influence on ruminal fermentation of finishing beef cattle than peNDF, with potential implications for ruminal health.

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: Observational · Consensus signal: none
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 communication0.0010.000
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 head0.021
GPT teacher head0.314
Teacher spread0.293 · 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 designObservational
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

Citations0
Published2025
Admission routes1
Has abstractyes

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