Effect of development system on growth and reproductive performance of beef heifers1,2
Bibliographic record
Abstract
Reproductive performance was evaluated in beef heifers born over a 2-yr period to determine the effects of target breeding weight (TBW) and development system (SYS) on growth and subsequent reproductive efficiency. Spring-born Angus heifers (253 ± 0.7 kg) were randomly allocated over 2 consecutive yr (yr 1, n = 80; yr 2, n = 96) to be developed to either 55% (350 kg) of mature BW (moderate gain, MG) or 62% (395 kg) of mature BW (high gain, HG). Each MG and HG group was further assigned to 1 of 2 replicated systems: (1) bale graze bromegrass-alfalfa round bales in field paddocks (BG) or (2) fed bromegrass-alfalfa round bales in drylot pens (DL). Heifers were fed a diet of bromegrass-alfalfa hay (56.9% TDN; 9.8% CP) and barley grain supplement (85.1% TDN; 12.3% CP). After the 202-d development period, heifers were exposed to bulls for a 63-d breeding season. Target BW × SYS interactions were not detected for any measured parameters. During the winter development period, MG heifers had lower (P = 0.01) ADG than HG heifers and MG heifers had lighter (P = 0.01) BW at breeding. The proportion of heifers attaining puberty by 14.5 mo of age was less (P = 0.05) in MG (20 ± 4%) than HG heifers (52 ± 3%). From the end of the 202-d development period to pregnancy diagnosis, ADG was greater (P = 0.04) in MG heifers than HG heifers (0.83 vs. 0.71 kg/d). First-calf pregnancy rates were 86 and 88% for MG and HG heifers, respectively (P = 0.41). Second- and third-calf pregnancy rates of cows, developed in either a MG or HG system as heifers, were not different (P = 0.74; 94.7 vs. 95.9% and 93.8 vs. 93.9%, respectively). Economic analysis revealed a $58 reduced development cost for heifers developed to 55% compared with 62% of mature BW without a loss in reproductive performance.
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 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 | 0.002 | 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 | 0.001 |
| 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".