Impact of selection for residual feed intake on breeding soundness and reproductive performance of bulls on pasture-based multisire mating1
Bibliographic record
Abstract
There is concern in the beef industry that selecting bulls for feed efficiency based on residual feed intake (RFI) may have a negative impact on bull reproductive performance and fertility. Here we investigated the impact of selection of bulls for low RFI on breeding soundness evaluation (BSE), reproductive performance, and fertility of bulls under natural service in multisire mating groups on pasture. Of the 412 RFI-tested bulls available, 98 (23.8%) were culled for performance, type, temperament, or other reasons, and 88 (21.4%) were culled for failing BSE, for an overall cull rate of 45.1%. From among the 314 bulls subjected to BSE, 32 (10.2%), 20 (6.4%), and 36 (11.4%) were culled for poor feet and legs, scrotal circumference, and semen quality, respectively. The BSE traits were not different (P > 0.10) between bulls categorized as either inefficient (+RFI) or efficient (-RFI), but the proportion of bulls that failed to meet the 60% minimum sperm motility requirement tended (P = 0.07) to be greater in the -RFI group than in the +RFI group (10.2% vs. 4.4%, respectively). In a subpopulation of 115 bulls, individual progressive sperm motility was greater (P < 0.05) in +RFI (85%) than -RFI (80%) bulls. A multisire natural mating experiment was conducted during 2 consecutive breeding seasons (2006 to 2007 and 2007 to 2008) using 18 +RFI and 18 -RFI bulls. The overall calving rate (calves born/cows exposed) was 72.9%. Mean number of progeny per sire was significantly greater (P < 0.01) in -RFI bulls (18.3) than in +RFI bulls (11.8). Selection for feed efficiency based on RFI appears to have no detrimental impact on reproductive performance and fertility in beef bulls bred in multisire groups on pasture. However, the decreased sperm motility and the greater number of progeny per sire associated with -RFI status need further investigation.
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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 | 0.001 | 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".