0660 Reduced enteric methane emissions on legume versus grass irrigated pastures
Bibliographic record
Abstract
Life cycle assessment that compared the cow–calf and feedlot phases of beef production in western Canada demonstrated that the greatest source of greenhouse gas emissions, in carbon dioxide equivalents (CO2 eq.), was enteric methane (CH4). Furthermore, the cow–calf phase was responsible for approximately 80% of CO2 eq. Perennial legume forages contain less fiber than grasses and are, therefore, more digestible, and condensed tannins (CT) have been reported to reduce ruminant enteric methane emissions. Our objective was to measure enteric CH4 emissions of beef cows and heifers grazing irrigated pastures. We compared a grass with two nonbloating legumes, one that had CT and one that did not. Our treatments were meadow bromegrass (Bromus riparius Rehmann), CT-containing birdsfoot trefoil (Lotus corniculatus L.), and non-CT cicer milkvetch (Astragalus cicer L.). The study was a randomized complete block design with 5 replications. The experimental unit was a 0.365-ha rotationally stocked pasture containing one forage treatment and one cow in late gestation (616 ± 8 kg; 2014) or two heifers (each 439 ± 7 kg; 2015). Following a 5- (2014) or 2-wk (2015) adjustment period, enteric methane was sampled on 4 d/wk for 5 wk on 1 (2014) or 2 (2015) reps/wk using the sulfur hexafluoride method (Johnson et al., 2007). Forage disappearance from pastures was estimated from pre- minus postgrazing herbage DM, measured using a rising plate meter calibrated for each species. This value is presented as percent of BW. The herbage of the cultivar of birdsfoot trefoil used in this study, Langille, contained 20 to 30 mg CT/g DM whereas the CT concentration of the other two pasture species was negligible. We conclude that methane emissions were reduced by approximately half for cows grazing legumes compared with grass and by approximately one-third for heifers grazing legumes compared with grass. However, there did not appear to be an effect of CT on enteric CH4 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 | 0.000 | 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".