Application of 3-nitrooxypropanol and canola oil to mitigate enteric methane emissions of beef cattle results in distinctly different effects on the rumen microbial community
Bibliographic record
Abstract
Abstract Background: The major GHG from ruminants is enteric methane (CH4) which in 2010, was estimated at 2.1 Gt of CO2 equivalent, accounting for 4.3% of global GHG emissions. There re extensive efforts being made around the world to develop methane mitigating inhibitors that specifically target rumen methanogens with the ultimate goal of reducing the environmental footprint of ruminant livestock production. This study examined the individual and combined effects of supplementing a high-forage diet (90% barley silage) fed to beef cattle with the investigational methane (CH4) inhibitor 3-nitrooxypropanol (3-NOP) and canola oil (OIL) on the rumen microbial community in relation to enteric CH4 emissions and ruminal fermentation.Results: 3-NOP and OIL individually reduced enteric CH4 emission (-28.2% and -24.0%, respectively), and the effects were additive when used in combination (-51.3%). 3-NOP increased H2 emissions 37 fold, while co-administering 3-NOP and OIL increased H2 in the rumen 20-fold relative to the control diet. The inclusion of 3-NOP or OIL reduced the diversity of the rumen microbiome. 3-NOP resulted in targeted changes in the microbiome decreasing the relative abundance of Methanobrevibacter and increasing the relative abundance of Bacteroidetes. The inclusion of OIL resulted in large scale changes to the microbial community that were associated with changes in ruminal volatile fatty acid concentration and gas production. OIL significantly reduced the abundance of protozoa and fiber-degrading microbes in the rumen but it did not selectively alter the abundance of rumen methanogens.Conclusions: Our data provide a mechanistic understanding of CH4 inhibition by 3-NOP and OIL when fed alone and in combination to cattle. 3-NOP specifically targeted rumen methanogens inhibiting the hydrogenotrophic methanogenesis pathway and resulting in increased H2 emissions and propionate production. In contrast, OIL caused large scale changes in the rumen microbial community by indiscriminately altering the abundance of a range of rumen microbes, reducing the abundance of fibrolytic bacteria and altering rumen fermentation. Importantly, our data suggests that co-administering CH4 inhibitors with distinct mechanisms of action can both enhance CH4 inhibition and provide alternative sinks to prevent excessive accumulation of ruminal H2.
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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) | 0.001 | 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".