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Record W4281990273 · doi:10.1186/s42523-022-00179-8

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

2022· article· en· W4281990273 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAnimal Microbiome · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRuminant Nutrition and Digestive Physiology
Canadian institutionsAgriculture and Agri-Food Canada
FundersDSM Nutritional ProductsGénome QuébecAgriculture and Agri-Food CanadaNational Natural Science Foundation of ChinaMcGill University
KeywordsCanolaMethane emissionsRumenBeef cattleMethaneFood scienceAnimal scienceEnvironmental scienceChemistryBiologyBiotechnologyEcologyFermentation

Abstract

fetched live from OpenAlex

Abstract Background The major greenhouse gas from ruminants is enteric methane (CH 4 ) which in 2010, was estimated at 2.1 Gt of CO 2 equivalent, accounting for 4.3% of global anthropogenic greenhouse gas emissions. There are extensive efforts being made around the world to develop CH 4 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 CH 4 inhibitor 3-nitrooxypropanol (3-NOP) and canola oil (OIL) on the rumen microbial community in relation to enteric CH 4 emissions and ruminal fermentation. Results 3-NOP and OIL individually reduced enteric CH 4 yield (g/kg dry matter intake) by 28.2% and 24.0%, respectively, and the effects were additive when used in combination (51.3% reduction). 3-NOP increased H 2 emissions 37-fold, while co-administering 3-NOP and OIL increased H 2 in the rumen 20-fold relative to the control diet. The inclusion of 3-NOP or OIL significantly 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 substantial 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 CH 4 inhibition by 3-NOP and OIL when offered alone and in combination to cattle fed a high forage diet. 3-NOP specifically targeted rumen methanogens and partly inhibited the hydrogenotrophic methanogenesis pathway, which increased H 2 emissions and propionate molar proportion in rumen fluid. In contrast, OIL caused substantial changes in the rumen microbial community by indiscriminately altering the abundance of a range of rumen microbes, reducing the abundance of fibrolytic bacteria and protozoa, resulting in altered rumen fermentation. Importantly, our data suggest that co-administering CH 4 inhibitors with distinct mechanisms of action can both enhance CH 4 inhibition and provide alternative sinks to prevent excessive accumulation of ruminal H 2 .

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.448
Threshold uncertainty score0.244

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.016
GPT teacher head0.230
Teacher spread0.214 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it