Effect of low and high forage diet on enteric and manure pack greenhouse gas emissions from a feedlot
Bibliographic record
Abstract
The objectives of this study were to assess enteric methane (CH4) production by beef steers fed one of two isocaloric diets with different forage:grain ratios and to quantify greenhouse gas (GHG) emissions from bedded manure packs in the eight feedlot pens holding these steers (14 head pen-1). Five animals (252 ± 20 kg) in each pen were randomly selected for measurement of CH4 emissions over the course of the 126-d feeding trial. Two 24-h gas collections were completed for each steer in each of three collection periods using the sulfur hexafluoride tracer gas technique. The fluxes of nitrous oxide (N2O), methane (CH4) and carbon dioxide (CO2) from bedding packs were measured using vented static chambers in each sampling period. Methane production (L d-1) was 42% higher (P < 0.05) from steers fed the low forage:grain ratio than from steers fed the high forage:grain ratio. Overall, methane production (% of gross energy intake) ranged from 0.9 to 6.9% on the low forage:grain diet and from 0.7 to 4.9% on the high forage:grain diet. Daily CH4 emissions were similar in the first two periods and increased during the third sampling period. There was no effect of diet on manure pack temperature during sampling, however, the manure pack was deeper (P < 0.05) in pens holding animals fed the high forage:grain diet. Furthermore, diet had no effect on the manure pack fluxes. Total daily non-CO2 emissions from enteric and manure pack sources (CO2 equivalent) were different (P < 0.05) between dietary treatments and averaged 1931 ± 81 g head-1 d-1 for the low forage:grain and 1394 ± 81 g head-1 d-1 for the high forage:grain diet. Key words: Feedlot steers, greenhouse gases, enteric fermentation, manure packs
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".