Use of corn distillers’ dried grains to reduce enteric methane loss from beef cattle
Bibliographic record
Abstract
There are significant emissions of greenhouse gases (GHG) from agriculture, and a major source is enteric methane (CH 4 ) from ruminants. Our study reports the impact on enteric CH 4 emissions when barley grain (35% of the dietary dry matter (DM) was replaced by corn distillers’ dried grains with solubles (DDGS, adding 30 g fat kg -1 dietary DM) in the backgrounding diet of growing beef cattle. The addition of DDGS reduced CH 4 emissions (g d -1 ) by 19.9%, and by 16.4% when adjusted for DM intake [g (DM intake) -1 ] or by 23.9% when adjusted for gross energy (GE) intake (% of GE intake). Adding DDGS to cattle diets reduced CH 4 emissions, but the effects of higher N content of the manure on emissions of nitrous oxide and ammonia need to be accounted for to complete the evaluation of the environmental impact of feeding DDGS to feedlot cattle. Key words: Methane, beef cattle, corn distillers’ dried grains with solubles, lipid, greenhouse gas emissions, sulphur hexafluoride
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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 | 0.001 |
| 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".