Implications of dairy systems on enteric methane and postulated effects on total greenhouse gas emission
Bibliographic record
Abstract
The effects of feeding total mixed ration (TMR) or pasture forage from a perennial sward under a management intensive grazing (MIG) regimen on grain intake and enteric methane (EM) emission were measured using chambers. Chamber measurement of EM was compared with that of SF6 employed both within chamber and when cows grazed in the field. The impacts of the diet on farm gate greenhouse gas (GHG) emission were also postulated using the results of existing life cycle assessments. Emission of EM was measured in gas collection chambers in Spring and Fall. In Spring, pasture forage fiber quality was higher than that of the silage used in the TMR (47.5% v. 56.3% NDF; 24.3% v. 37.9% ADF). Higher forage quality from MIG subsequently resulted in 25% less grain use relative to TMR (0.24 v. 0.32 kg dry matter/kg milk) for MIG compared with TMR. The Fall forage fiber quality was still better, but the higher quality of MIG pasture was not as pronounced as that in Spring. Neither yield of fat-corrected milk (FCM) which averaged 28.3 kg/day, nor EM emission which averaged 18.9 g/kg dry matter intake (DMI) were significantly affected by diet in Spring. However, in the Fall, FCM from MIG (21.3 kg/day) was significantly lower than that from TMR (23.4 kg/day). Despite the differences in FCM yield, in terms of EM emission that averaged 21.9 g/kg DMI was not significantly different between the diets. In this study, grain requirement, but not EM, was a distinguishing feature of pasture and confinement systems. Considering the increased predicted GHG emissions arising from the production and use of grain needed to boost milk yield in confinement systems, EM intensity alone is a poor predictor of the potential impact of a dairy system on climate forcing.
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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".