Effect of pasture type (alfalfa vs. grass) on methane and carbon dioxide production by yearling beef heifers
Bibliographic record
Abstract
The objective of this study was to determine effect of pasture type on methane and carbon dioxide production by heifers grazing alfalfa or grass pastures at three sites across western Canada. All pastures were intensively managed so that heifers had ad libitum access to new forage material each day, and pastures were back-fenced to prevent the heifers accessing previously grazed areas. As measured using the sulfur hexafluoride (SF 6 ) tracer technique, total methane production at the Brandon, MB, and Swift Current, SK, sites was unaffected by pasture type (averaging 157.4 g CH 4 head -1 d -1 ), whereas at Lethbridge, AB, heifers grazing alfalfa produced more methane than did those on the grass pasture (162.8 vs. 113.5 g CH 4 head -1 d -1 ; P < 0.05). Calculated with dry matter intake (DMI) estimated by alkane analysis, methane production per unit DMI was 3 9% lower from heifers consuming grass compared with alfalfa (P < 0.001). When intakes were estimated by the Cornell Net Carbohydrate and Protein System (CNCPS) model, CH 4 production kg -1 DMI did not differ (P > 0.05) between pasture types. Loss of gross energy intake (GEI) to methane, as estimated by alkane analysis, was 6.9% for heifers grazing grass, and 9.6% for heifers grazing alfalfa (P < 0.001). Calculated using CNCPS, losses were similar (P > 0.05) between grass and alfalfa (5.8 vs. 6.2% of GEI, respectively). Carbon dioxide production per unit DMI did not differ between pasture types, irrespective of method used to estimate intake (alkanes or CNCPS). The method used to predict intake can have a major influence on calculated values when methane emissions are expressed as a percentage of GEI in grazing ruminants. At each site, CH 4 emissions and in vitro digestibility of the forage were influenced by the composition of the stand and the maturity of the forage at the time of harvest. Key words: Alfalfa, grass, grazing, legume, methane emissions
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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 | 0.001 | 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".