Beef cattle grazing behaviour differs among diploid and tetraploid crested wheatgrasses (<i>Agropyron cristatum</i>and<i>A. desertorum</i>)
Bibliographic record
Abstract
Iwaasa, A. D., Jefferson, P. G. and Birkedal, E. J. 2014. Beef cattle grazing behaviour differs among diploid and tetraploid crested wheatgrasses (Agropyron cristatum and A. desertorum). Can. J. Plant Sci. 94: 851–855. A study was conducted over 4 yr (1999, 2000, 2002 and 2003) at Swift Current to evaluate the forage preferences of steers grazing five different crested wheatgrass (CWG) cultivars: Kirk (2n=28), Fairway (2n=14) and Parkway (2n=14) [Agropyron cristatum (L.) Gaertn.], Hycrest (2n=28) (A. cristatum×A. desertorum) and Nordan (2n=28) [(A. desertorum (Fisch. Ex Link) Schult.)]. Animal grazing frequencies for each CWG cultivar patch were converted to percentages (Grazing%) for each grazing time period. Grazing% for Kirk and Hycrest CWGs were similar with Nordan having higher (P<0.05) Grazing% compared with the hybrid and diploid CWGs. Contrasts revealed no differences (P=0.48) in Grazing% between diploid versus hybrid cultivars, while higher (P<0.01) Grazing% were observed for tetraploid compared with diploid and hybrid CWG cultivars. For forage nutritive values, significant Cultivar (P<0.01) and Year (P<0.0001) main effects were observed. Overall mean values for percent crude protein (%CP) and percent acid detergent fibre (%ADF) for Nordan, Kirk, Hycrest, Fairway and Parkway were 10.6±0.3 and 29.2±0.4, 11.0±0.3 and 28.7±0.4, 10.4±0.3 and 29.7±0.4, 9.9±0.3 and 28.5±0.4, and 10.0±0.3 and 28.7±0.4, respectively (± SE). Correlation coefficients between Grazing% and all nutritive value constituents were low and not significant. This study observed grazing preference differences among different CWG cultivars that may lead to grazing management strategies to improve pasture utilization potential and animal production.
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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 | 0.000 |
| 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) | 0.001 | 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".