Effects of supplementing spring-calving beef cows grazing barley crop residue with canola meal and wheat-based dry distillers grains with solubles on performance, reproductive efficiency, and system cost
Bibliographic record
Abstract
A 2-yr experiment was conducted to determine the effects of supplementing canola meal and wheat-based dry distillers grains with solubles (wDDGS) on the performance of wintering cows grazing barley straw-chaff. Each year, a 24-ha field was seeded with forage barley ( Hordeum vulgare ‘Ranger'). The mature crop was swathed and combined to collect straw-chaff crop residue (STCH; 5.7% CP, 51% TDN) in 22 ± 5 kg piles. The field was divided into six 4-ha paddocks. Each year, 60 pregnant Black Angus cows (yr 1: BW=641.4±10.6 kg, BCS=2.7 ± 0.1, gestation d=121 ± 2; yr 2: BW=685.2±9.1 kg, BCS=2.6 ± 0.1, gestation d=108 ± 2) were randomly allocated to 1 of 3 replicated (n = 2) supplement treatments: (1) 100% wDDGS (39.2% CP, 78.8% TDN, DM basis); (2) 50% wDDGS plus 50% canola meal (50:50); or (3) 100% canola meal (42.6% CP, 71.5% TDN, DM basis) while winter grazing (49 and 39 d for yr 1 and yr 2, respectively) on STCH piles. The supplementation rate was 0.41% of BW or 2.6 kg/d. Supplementation strategy did not influence ( P > 0.05) STCH DMI (11.4±0.55 kg/d), cow BW change (−3.0±1.90 kg), final BCS (2.5 ± 0.02), and subsequent reproductive performance. The results indicate that approximately one quarter (24–28%) of the winter feeding period can be filled by grazing barley STCH residue with supplementation and that canola meal was equal to wDDGS as a supplement for beef cows consuming barley STCH residue.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".