MétaCan
Menu
Back to cohort
Record W1973935249 · doi:10.1071/ea08083

Brahman and Brahman crossbred cattle grown on pasture and in feedlots in subtropical and temperate Australia. 3. Feed efficiency and feeding behaviour of feedlot-finished animals

2009· article· en· W1973935249 on OpenAlexfundno aff
K. M. Schutt, P. F. Arthur, H. M. Burrow

Bibliographic record

VenueAnimal Production Science · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic and phenotypic traits in livestock
Canadian institutionsnot available
FundersMeat and Livestock AustraliaMcMaster University
KeywordsBrahmanAnimal scienceFeedlotShorthornBiologySireCrossbreedEnvironmental management systemBeef cattleFeed conversion ratioTemperate climateHumid subtropical climateVeterinary medicineAgronomyIrrigationBody weightBreedBotany

Abstract

fetched live from OpenAlex

The objective of this experiment was to quantify differences in feed efficiency and feeding behaviour of 470 heifers and steers by Brahman, Belmont Red, Santa Gertrudis, Angus, Hereford, Shorthorn, Charolais and Limousin sires mated to Brahman dams. Animals were bred in subtropical Queensland and finished in a temperate New South Wales feedlot. Animals averaged 598 days of age and 425.8 kg at the start of the feed intake test period. Sire breeds did not differ for eating rate, feed conversion ratio or relative growth rate. Generally, higher daily feed intakes (DFI) corresponded with higher average daily gains (ADG). Straightbred Brahmans fed the most frequently (16.6 ± 0.8 sessions/day; P < 0.05) but spent the least time eating of all breeds (67.4 ± 2.7 min/day; P < 0.001). Least squares means for Brahman, Belmont Red, Santa Gertrudis, Angus, Hereford, Shorthorn, Charolais and Limousin sired progeny, respectively, for residual feed intake (RFI; P < 0.05) were 0.02 ± 0.16, 0.14 ± 0.13, –0.10 ± 0.23, 0.54 ± 0.17, –0.27 ± 0.18, 0.29 ± 0.18, –0.46 ± 0.16 and –0.21 ± 0.13 kg/day, and for ADG (P < 0.001) were 1.06 ± 0.05, 1.17 ± 0.04, 1.52 ± 0.08, 1.47 ± 0.06, 1.46 ± 0.06, 1.46 ± 0.06, 1.35 ± 0.06 and 1.38 ± 0.05 kg/day. While straightbred Brahmans did not differ from all other sire breeds for RFI, their lower appetite relative to crossbred contemporaries resulted in the lowest DFI (P < 0.001) and lowest ADG (P < 0.001) overall. Angus sired crosses were the least efficient feeders and spent the most time eating, consumed the most feed and had the highest RFI, but were not significantly different to Santa Gertrudis and Shorthorn crosses for these traits. Angus sired crosses spent 24.1 and 15.4 min/day more time eating (P < 0.001) than straightbred Brahmans and Charolais crosses, and consumed 35 and 13% more feed (P < 0.001) respectively. Charolais sired crosses were the most feed efficient with the lowest RFI and intermediate DFI, and did not differ significantly from the highest ranking sire breeds for ADG or Kleiber ratio. While Belmont Red crosses did not differ from all breeds for RFI, they had significantly lower DFI than British and Santa Gertrudis crosses resulting in lower ADG (P < 0.001) relative to these sire breeds. Therefore, selection of Charolais, Hereford, Limousin and Santa Gertrudis sire breeds would result in the most feed efficient (low RFI) crosses with Brahman without any sacrifice in ADG.

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 score0.014
Threshold uncertainty score0.028

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 head0.020
GPT teacher head0.286
Teacher spread0.266 · 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

Citations18
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueAnimal Production ScienceSame topicGenetic and phenotypic traits in livestockFrench-language works237,207