Severe below-maintenance feed intake increases methane yield from enteric fermentation in cattle
Bibliographic record
Abstract
Abstract The relationship between feed intake at production levels and enteric CH 4 production in ruminants consuming forage-based diets is well described and considered to be strongly linear. Unlike temperate grazing systems, the intake of ruminants in rain-fed tropical systems is typically below maintenance requirements for part of the year (dry seasons). The relationship between CH 4 production and feed intake in animals fed well below maintenance is unexplored, but changes in key digestive parameters in animals fed at low levels suggest that this relationship may be altered. We conducted a study using Boran yearling steers ( n 12; live weight: 162·3 kg) in a 4 × 4 Latin square design to assess the effect of moderate to severe undernutrition on apparent digestibility, rumen turnover and enteric CH 4 production of cattle consuming a tropical forage diet. We concluded that while production of CH 4 decreased (1133·3–65·0 g CH 4 /d; P < 0·0001), over the range of feeding from about 1·0 to 0·4 maintenance energy requirement, both CH 4 yield (29·0−31·2 g CH 4 /kg DM intake; P < 0·001) and CH 4 conversion factor ( Y m 9·1–10·1 MJ CH 4 /MJ gross energy intake; P < 0·01) increased as intake fell and postulate that this may be attributable to changes in nutrient partitioning. We suggest there is a case for revising emission factors of ruminants where there are seasonal nutritional deficits and both environmental and financial benefits for improved feeding of animals under nutritional stress.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".