Rapid Communication: Evaluation of methane inhibitor 3-nitrooxypropanol and monensin in a high-grain diet using the rumen simulation technique (Rusitec)1,2
Bibliographic record
Abstract
The objective of this study was to evaluate the effects of 3-nitrooxypropanol (NOP), a known methane (CH4) inhibitor; the ionophore monensin (MON); and their combination on in vitro CH4 production in a high-grain diet (85% barley grain, 10% barley silage, and 5% vitamin-mineral supplement; DM basis) using a rumen simulation technique (Rusitec). Sixteen fermentation vessels in 2 Rusitec apparatuses (blocks) were used in a completely randomized block design with 4 treatments: Control, NOP (200 µg/g DM), MON (200 µg/g DM), and the combination of 200 µg NOP/g DM and 200 µg MON/g DM (NOP + MON). Two fermenters within each apparatus were randomly assigned to a treatment. Treatments were mixed with 10 g of substrate and supplied on a daily basis. The study included an 8-d adaptation period without treatment supplementation and a 6-d period for addition of treatments. Dry matter disappearance, pH, and total VFA were not affected by treatment (P ≥ 0.34). Acetate proportion was decreased by 8.3% and 14.9% with NOP and NOP + MON (P < 0.01), respectively; however, propionate proportion was not affected by treatment (P = 0.44). The acetate to propionate ratio was lowered by 21.1% with the combination of NOP and MON (P = 0.02), whereas ammonia-N concentration was not affected by treatment (P = 0.50). Total gas production was unaffected (P = 0.50), but CH4 production decreased by 77.7% and 75.95% (P < 0.01) with NOP and NOP + MON addition, respectively. Concurrently, H2 gas production increased by 131.3% and 185.6% (P = 0.01) with NOP and NOP + MON treatments, respectively. The copy number of methanogens was decreased in both solid and liquid phases (P < 0.01) with NOP and NOP + MON treatments. Despite the combination of NOP + MON showing the greatest decrease in acetate molar proportion and acetate to propionate ratio, it did not further inhibit CH4 beyond the effect of NOP alone. The decrease in CH4 emissions with treatments that included NOP occurred along with a decrease in the copy number of methanogens associated with the solid and liquid phases, confirming the inhibitory effects of NOP on these microorganisms. In conclusion, the combined effects of NOP and MON on CH4 mitigation did not exceed the effect of NOP alone when using a high-grain diet in vitro.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".