Genetic parameters and genotype × environment interaction for feed efficiency traits in steers fed grower and finisher diets1
Bibliographic record
Abstract
The objective of this study was to examine the genetic parameters and genetic correlations of feed efficiency traits in steers (n = 490) fed grower or finisher diets in 2 feeding periods. A bivariate model was used to estimate phenotypic and genetic parameters using steers that received the grower and finisher diets in successive feeding periods, whereas a repeated animal model was used to estimate the permanent environmental effects. Genetic correlations between the grower-fed and finisher-fed regimens were 0.50 ± 0.48 and 0.78 ± 0.43 for residual feed intake (RFI) and G:F, respectively. The moderate genetic correlation between the 2 feeding regimens may indicate the presence of a genotype × environment interaction for RFI. Permanent environmental effects (expressed in percentage of phenotypic variance) were detected in the grower-fed steers for ADG (38%), DMI (30%), RFI (18%), and G:F (40%) and also in the finisher-fed steers for ADG (28%), DMI (35%), metabolic mid-weight (23%), and RFI (10%). Heritability estimates were 0.08 ± 0.10 and 0.14 ± 0.15 for the grower-fed steers and 0.42 ± 0.16 and 0.40 ± 17 for the finisher-fed steers for RFI and G:F, respectively. The dependency of the RFI on the feeding regimen may have serious implications when selecting animals in the beef industry. Because of the higher cost of grains, feed efficiency in the feedlot might be overemphasized, whereas efficiency in the cow herd and the backgrounding segments may have less emphasis. These results may also favor the retention (for subsequent breeding) of cows whose steers were efficient in the feedlot sector. Therefore, comprehensive feeding trials may be necessary to provide more insight into the mechanisms surrounding genotype × environment interaction in steers.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".