Genetic parameters for production and feeding behaviour traits in crossbred steers fed a finishing diet at different ages
Bibliographic record
Abstract
Durunna, O. N., Mujibi, F. D. N., Nkrumah, D. J., Basarab, J. A., Okine, E. K., Moore, S. S. and Wang, Z. 2013. Genetic parameters for production and feeding behaviour traits in crossbred steers fed a finishing diet at different ages. Can. J. Anim. Sci. 93: 79–87. Because cattle can be raised postweaning under several feeding regimes, this study examined the consistency of phenotypic and genetic parameters of some production and feeding behaviour traits between two feeding periods that beef cattle received a finisher diet. Crossbred steers (n=851) were used for feeding trials from 2002 to 2009 where the steers received a finisher diet either during the fall–winter season (FP1) or during the winter–spring season (FP2). The steers evaluated in FP2 received a backgrounding diet in FP1. Traits examined include dry matter intake (DMI), average daily gain (ADG), gain: feed ratio (G:F), residual feed intake (RFI), and ultrasound measures of backfat thickness (UBF), rib-eye area (UREA) and marbling (UMB). Others include feeding duration (FD), headdown time (HDT) and feeding frequency (FF). As expected, there was no difference (P=0.90) between the RFI measured in the two periods. The two periods were similar for UBF (P=0.87) and UREA (P=0.25),while DMI, ADG and UMB were greater (P<0.04) in FP2 than in FP1. The FD, HDT and FF were greater (P<0.0001) in FP1 compared with FP2. Heritability estimates were calculated in FP1 and FP2, respectively, for ADG (0.38, 0.28), DMI (0.52, 0.42), RFI (0.16, 0.27), G:F (0.18, 0.33), HDT (0.35, 0.18) and FF (0.26, 0.46). More importantly, genetic correlations between FP1 and FP2 were estimated for DMI (0.61), RFI (0.65) and G:F (0.60). The results may indicate the influence of age or feeding period or both on these traits, which may suggest the need for multi-environment genetic evaluations to identify superior animals.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".