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Record W4402541814 · doi:10.1093/jas/skae234.762

PSLBII-5 Impacts of residual feed intake measured as a heifer in drylot on mature cows and calves grazing native pasture

2024· article· en· W4402541814 on OpenAlexaffabout
Francisco Novais, Hailey Bolen, Valentine Udeh, Sydney G. Lopes, Temitope Oloyede, Le Luo Guan, Changxi Li, J. A. Basarab, Carolyn Fitzsimmons, Edward W. Bork

Bibliographic record

VenueJournal of Animal Science · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRuminant Nutrition and Digestive Physiology
Canadian institutionsUniversity of British ColumbiaAgriculture and Agri-Food CanadaUniversity of Alberta
Fundersnot available
KeywordsGrazingPastureResidual feed intakeAnimal scienceBiologyAgronomyBeef cattleBody weightFeed conversion ratioEndocrinology

Abstract

fetched live from OpenAlex

Abstract Selection for feed efficiency is crucial for improving economic and environmental sustainability in beef cattle production. Residual feed intake (RFIfat) is a commonly used measure of feed efficiency and is determined in a drylot setting by calculating the difference between observed and expected dry matter intake (DMI), where expected feed intake is adjusted for metabolic body weight (BW), average daily gain (ADG) and body fatness. Lower RFIfat cattle are more efficient animals as they eat less than predicted for the same growth, body size and body fatness. Limited studies have been conducted evaluating the role of RFIfat on the subsequent performance of cow-calf pairs on native range. Kinsella Composite cows and calves (n = 120) grazed native pasture from July 11 to Sept 12 (summer) and from Sept 13 to Nov 2 (fall) of 2023 were included in this study. All dams had previously been evaluated for RFIfat as a heifer (8 to 12 mo of age) using the GrowSafe Feed Intake System (Vytelle, Canada). Cow and calf ADG were subjected to an analysis of covariance using lm function from stats R core package (R Core Team, 2024), with cow age (2 to 8 yr of age) as the fixed effect and RFIfat as the covariate, analyzing separately by season. An unbalanced Tukey HDS post-hoc were applied for age and p-values < 0.05 were considered significant. Weight gain was assessed on cows with an initial BW on pasture of 598.4 ± 68.4 kg, and 2 to 8 yr of age, and on calves having an initial on pasture BW of 106 ± 21.5 kg, and 65 ± 14 d of age. Cow age affected (P < 0.01) cow ADG during summer, with the youngest dams (2 yr old) gaining more weight than older animals (7 yr old; Figure 1A). No effect of RFIfat was found on cow weight gain during summer grazing. However, during fall grazing, RFIfat affected (P < 0.01) cow ADG (Figure 1B). Low-RFIfat cows (efficient) had increased weight gain during fall grazing as compared with high-RFIfat cows (inefficient: Figure 1B). Calf ADG was not affected (P > 0.1) by cow age, cow RFIfat and cow ADG during summer and fall. We conclude that cows with low RFIfat exhibited superior body weight gain, during fall grazing on native range when forage nutrient quality and quantity become limiting.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0020.000

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 head0.026
GPT teacher head0.282
Teacher spread0.255 · 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
Published2024
Admission routes2
Has abstractyes

Explore more

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