Enteric methane emissions from growing beef cattle as affected by diet and level of intake
Bibliographic record
Abstract
A study was conducted to determine whether enteric methane (CH 4 ) emissions from growing feedlot cattle fed backgrounding diets based on barley silage could be reduced through grain supplementation. A second objective was to determine the effects of feed intake on CH 4 emissions. Eight Angus beef heifers (initial and final body weight, 328 ± 28 and 430 ± 29 kg) were used. The experiment was designed as a split-plot crossover with two diets and two 8-week periods. The main plot was the diet [dry matter (DM) basis]: high forage (70% barley silage, 30% barley-based concentrate) or high grain (30% barley silage, 70% corn-based concentrate). The sub-plot was the feeding level: unrestricted (ad libitum feed intake, 5% orts) or restricted (65% of ad libitum intake) feed intake. Methane emissions were measured during each sub-plot over 3 d using whole animal chambers. Changing the forage to concentrate ratio and substituting barley for corn did not affect CH 4 emissions (141.5 g d -1 ; P = 0.26), and the average emission was about 10% higher than the emission calculated using the International Panel on Climate Change (IPCC) Tier 1 approach. Methane conversion rate was also similar for both diets [6.23% of gross energy intake (GEI), P = 0.29], and was similar to the value of 6.0 used in the IPCC Tier 2 approach to calculating CH 4 emissions from cattle. Restricting intake reduced CH 4 emissions (169 vs. 114 g d -1 ; P < 0.002), with the reduction in CH 4 proportional to the decline in intake. Level of intake relative to maintenance energy requirements was moderately inversely related (r = -0.30; P = 0.04) to CH 4 (% GEI). The proportion of GEI lost as CH 4 declined by 0.77 percentage units per unit increase in level of intake above maintenance. This study shows that supplementing barley-silage-based diets with corn grain to increase diet quality has only small effects on reducing CH 4 emissions. In contrast, maximizing feed intake above maintenance energy requirements increases daily CH 4 emissions, but improves efficiency of CH 4 conversion because CH 4 , as a percentage of GEI, declined. Thus, feeding cattle for maximum gain is an important CH 4 mitigation strategy for the cattle industry as it reduces the proportion of feed energy lost as CH 4 each day, as well as, reduces the number of days to market and associated CH 4 production. Key words: Cattle, methane, greenhouse gasses
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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".