Phenotypic and genetic relationships of feed efficiency with growth performance, ultrasound, and carcass merit traits in Angus and Charolais steers1
Bibliographic record
Abstract
Feed efficiency is of particular importance to the beef industry, as feed costs represent the single largest variable cost in beef production systems. Selection for more efficient cattle will lead to reduction of feed related costs, but should not have adverse impacts on quality of the carcass. In this study, we evaluated phenotypic and genetic correlations of residual feed intake (RFI), RFI adjusted for end-of-test ultrasound backfat thickness (RFIf), and RFI adjusted for ultrasound backfat thickness and LM area (RFIfr) with growth, ultrasound, and carcass merit traits in an Angus population of 551 steers and in a Charolais population of 417 steers. In the Angus steer population, the phenotypic and genetic correlation of RFI with carcass merit traits including HCW, carcass backfat, carcass LM area, lean meat yield, and carcass marbling were not significant or weak with correlations coefficients ranging from -0.0007 ± 0.05 to 0.18 ± 0.21. In the Charolais steer population, the phenotypic and genetic correlations of RFI with the carcass merit traits were also weak, with correlation coefficients ranging from -0.07 ± 0.06 to 0.19 ± 0.18, except for the genetic correlation with carcass average backfat, which was moderate with a magnitude of 0.42 ± 0.29. Inclusion of ultrasound backfat thickness in the model to predict the expected daily DMI for maintenance explained on average an additional 0.5% variation of DMI in the Angus steers and 2.3% variation of DMI in the Charolais steer population. Inclusion of both the ultrasound backfat and LM area in the model explained only 0.7% additional variance in DMI in the Angus steer population and only 0.6% in the Charolais steer population on top of the RFIf model. We concluded that RFIf adjusted for ultrasound backfat at the end of the test will lead to decreases of both the phenotypic and genetic correlations with carcass backfat and marbling score to a greater extent for late-maturing beef breeds such as Charolais than for early-maturing beef breeds such as Angus. However, further inclusion of ultrasound LM area on top of the final ultrasound backfat in the model of calculating RFI had little effect in reducing the correlations of RFI with the carcass merit traits.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".