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Record W4388540140 · doi:10.1093/jas/skad281.157

211 Evaluation of Beef Heifer Variability in the Ability to Eat and Digest a High Forage Diet

2023· article· en· W4388540140 on OpenAlexaff
Nikita A Payne, Greg B Penner, H.A. Lardner, D. Wade Abbott, Robert J. Gruninger, Gabriel O Ribeiro

Bibliographic record

VenueJournal of Animal Science · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRuminant Nutrition and Digestive Physiology
Canadian institutionsAgriculture and Agri-Food CanadaUniversity of Saskatchewan
Fundersnot available
KeywordsForageFecesAnimal scienceDry matterBeef cattleNeutral Detergent FiberSilageBiologyResidual feed intakeDigestion (alchemy)ChemistryFeed conversion ratioBody weightAgronomyEndocrinology

Abstract

fetched live from OpenAlex

Abstract This study evaluated beef heifers selected for high or low digestible fiber intake (DFI) and investigated its relationship with methane production, residual feed intake (RFI), and total tract digestibility. Sixteen recently weaned black Angus beef heifers (n = 8/treatment) were selected from a group 64 heifers (224 ± 17.2 kg) fed a high forage-based diet [70% barley silage:30% pelleted concentrate (DM basis)]. The 64 heifers were fed in 6 outdoor pens equipped with GrowSafe bunks to monitor feed intake for 60 d (14 d adaptation + 46 d for data collection). Individual fecal samples and BW, and feed samples were taken once weekly. Fecal samples were pooled by animal. Feed and fecal samples were analyzed for dry matter (DM), neutral detergent fibre (NDF), and undigested neutral detergent fiber (uNDF) content. The internal marker uNDF was used to estimate total tract diet DM and NDF digestibility. The 8 heifers with the greatest and the 8 with the least digestible NDF intake (g/kg BW0.75) were selected and used for methane measurements using the GreenFeed system (42 d) and in a total-tract digestibility trial with total fecal and urine collection using the same high forage based diet. Results from the GrowSafe selection trial indicated no differences between the average BW of low and high DFI heifers (264 vs. 274 kg, P = 0.20). Heifers selected for high DFI had greater (P < 0.01) DM and NDF intake (kg/d or % of BW), and digestibility (49.6 vs. 42.1% NDF digestibility). The heifer groups differed in RFI (P < 0.01), with high DFI categorized as inefficient (+0.84 RFI) and low DFI as efficient (-0.34 RFI). No differences in ADG were observed between low and high DFI heifers during this short 46 d study period (0.614 vs 0.773, P = 0.16). High DFI heifers had lower methane production than low DFI heifers (15.9 vs. 19.0 g/kg of DMI, P = 0.02). The results of the total-tract digestibility trial showed that the high DFI heifers had a greater DMI compared with the low DFI heifers (10.9 vs. 10.2 kg/d; P = 0.04). The DMI intake was not different between groups when expressed as a % of BW (2.06 vs 2.04, P = 0.65). There was also no difference observed for DM digestibility (73.0 vs 73.1%) between the two groups. It is important to note that in the digestibility study, the DMI was less than in the GrowSafe selection trial (2.5 vs 3.2% BW) and this may have influenced results. Heifers with high DFI were heavier than low DFI heifers (533 vs. 505, P = 0.02) during the digestibility trial. Results suggest that selecting heifers for high DFI may increase growth rate and reduce methane production.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.005

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 head0.052
GPT teacher head0.309
Teacher spread0.257 · 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
Published2023
Admission routes1
Has abstractyes

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