The effects of spring versus summer calving on beef cattle reproductive and growth performance in western Canada
Bibliographic record
Abstract
Durunna, O. N., Girardin, L. C., Scott, S. L., Robins, C., Block, H. C., Iwaasa, A. D., Khakbazan, M. and Lardner, H. A. 2014. The effects of spring versus summer calving on beef cattle reproductive and growth performance in western Canada. Can. J. Anim. Sci. 94: 259-271. The majority of beef producers in western Canada have adopted a spring calving system. Evaluating alternative calving systems such as summer calving may lead to better use of forage resources to optimize cow-calf productivity. In order to evaluate the impact of calving system on cow-calf productivity, 346 Hereford or Angus crossbred cows were used in a 3-yr research study (2007 to 2009) at Brandon, Manitoba; Swift Current, Saskatchewan and Lanigan, Saskatchewan. Cows were bred to calve from February to May (early-calving system, EC) or from May to August (late-calving system, LC). Each system was evaluated for effect on performance and reproductive efficiency. Forage yield, utilization and nutritive value were assessed. Cow body weights (BW), ultrasound measures of backfat and calf BW were evaluated at precalving, breeding and weaning. There was no difference between calving systems for pregnancy rate (P=0.13) EC (93.0%) vs. LC (95.8%); calving rate (P=0.89) EC (92.0%) vs. LC (91.7%) or proportion of calves born alive (P=0.85) EC (99.5%) vs. LC (99.6%). The average length of calving season was not different (P=0.26) between the two systems. The EC cows had greater (P=0.002) BW losses from calving to breeding but greater (P=0.001) BW gain from breeding to weaning than LC cows. Although calves born in LC had greater birth BW (P=0.003) than EC calves, calf weaning rate (P=0.01) and calf weaning BW (P<0.0001) were greater in EC. The higher weaning rate and higher weaning BW with EC has the potential to increase cow-calf productivity and may be more attractive to beef producers in western Canada.
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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".