Supplementation with crushed rapeseed causes reduction of methane emissions from lactating dairy cows on pasture
Bibliographic record
Abstract
The main objective of this study was to investigate the effect of supplementing a pasture diet with crushed rapeseed on enteric methane (CH4) emissions from lactating dairy cows. The experiment was conducted as a crossover design using eight multiparous lactating Norwegian red dairy cows [(means ± s.d.) 548 ± 52 kg bodyweight, 38 ± 14 days in milk and 35 ± 3.7 kg milk/day, at the start of the experiment] maintained in two groups and fed two diets in two periods with the second period extended (18 days) to investigate the persistence of the CH4 response. Four of the eight cows were fitted with a rumen cannula with two cannulated cows assigned to each group. Cows were maintained on pasture (24 h/day) with access to 9 kg/day of concentrate containing 10% crushed rapeseed (RSC) or a control concentrate (CC). Dietary fat content was 63 g/kg dry matter for RSC and 42 g/kg dry matter for CC. The CH4 production was measured for five consecutive days in each period using the sulfur hexafluoride tracer gas technique. Compared with CC, RSC caused a reduction in enteric CH4 emission (221 vs 251 g/day and 8.1 vs 9.0 g/kg of energy-corrected milk), and this response persisted in the extension period. Cows fed RSC had higher milk yield compared with cows fed CC (31.7 vs 29.6 kg/day). However, milk fat and protein content were lower in milk from cows fed RSC than CC. Therefore, energy-corrected milk was not affected by treatment. Feeding RSC lowered milk fat content of palmitic acid compared with CC. The study showed that adding crushed RSC to the diet can be an effective means of reducing CH4 emissions from lactating dairy cows on pasture, without negatively affecting milk production.
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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".