Strategies to Mitigate Enteric Methane Emissions in Ruminants: A Review
Bibliographic record
Abstract
Methane is the main greenhouse gas (GHG) emitted by ruminants. Mitigation strategies are required to alleviate this negative environmental impact while maintaining productivity and ruminants’ health. To date, numerous methane mitigation strategies have been investigated, reported and suggested by scientists to the livestock industry. In this review, the authors will focus on the commonly practiced and available techniques expanding the knowledge of the reader on the advances of methane mitigation strategies with a focus on the recent literature. Furthermore, the authors will attempt to discuss the drawbacks of the strategies in terms of animal health and performance reduction as well as the concept of feed and energy loss, adding an economic perspective to methane emission mitigation which is in the farmers’ direct interest. As a whole, many factors are effective in reducing undesired methane production, but this is definitely a complex challenge. Conclusively, further research is required to offer effective and efficient methane production mitigation solutions in ruminants worldwide, thus positively contributing to climate change.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".