Methane emissions and digestive physiology of non-lactating dairy cows fed pasture forage
Bibliographic record
Abstract
The objective of this study was to identify intake and digestion characteristic(s) responsible for variation in methane (CH4) emissions from non-lactating cows fed pasture forage. Nine Friesian × Jersey cows ranked low, medium or high CH4 emitters [group means 15.3, 19.2 and 24.8 g kg-1 dry matter intake (DMI), respectively; P = 0.015] were selected from a herd of 302 lactating cows. The selected cows were dried-off, rumen-fistulated, and fed indoors on fresh pasture forage at 0700 and 1700. Voluntary feed intake (VFI), feeding behaviour and intake rates (IR) were measured over 5 d. Feed allowance was reduced to 90% of VFI for measurement of CH4 emissions and rumen fermentation and digestion kinetics parameters. Although some variation in CH4 yield remained among the animals (26.4 ± 3.6 g kg-1 DMI), the previous ranking of cows during lactation was no longer evident during this study (P = 0.41). The change in CH4 yields may have resulted from lower feed intakes of lower quality pasture compared with grazing. Regression analysis showed that absolute CH4 emission (g d-1) was best described by DMI and rumen acetate concentration (ACE) before the PM feeding (ACE 1700) (R2 = 0.88), whereas CH4 yield (g kg-1DMI) was mainly a function of ACE 1700 h alone (R2 = 0.84). We suggest that large animal-to-animal variations in CH4 yield are most likely associated with high intakes and concomitant effects of salivation and rumen digestion and passage. Key words: Methane, animal variation, feed intake, rumen digestion, dairy cows, pasture
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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) | 0.000 | 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 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".