A meta-analysis of the effects of nitrate supplementation on enteric methane emission, production performance, and blood methemoglobin in dairy cattle
Bibliographic record
Abstract
This meta-analysis evaluated the effect of nitrate supplementation on enteric CH 4 emissions and performance in lactating dairy cows.A literature search identified 9 publications including 10 studies.Nitrate dose ranged from 5.3 to 21.1 g/kg DM and DMI was 19.7 ± 2.47 kg/d, milk yield (MY) was 28.1 ± 6.50 kg/d, and CH 4 production was 348 ± 50.5 g/d (mean ± SD).The mean difference between control and nitrate supplementation was analyzed using the metafor package in R, applying 3 random effects models.Model 1 estimated the overall mean difference across all studies regardless of dose (mean dose: 13.8 g nitrate/kg DM).Model 2 included factor effects of nitrate dose centered around the 2 most tested doses: mode dose of 10.2 ± 1.94 g nitrate/kg DM (n = 15) and high dose of 19.8 ± 2.51 g nitrate/kg DM (n = 10).Model 3 was a linear model evaluating the nitrate dose response.Model 1 showed that nitrate reduced CH 4 production by 20.3%, CH 4 yield (g/kg/DMI) by 16.4% and CH 4 intensity (g/kg ECM) by 20.1% compared with control.Model 2 showed a reduction of 21.5% and 18.7% in CH 4 production, 15.6% and 16.9% in CH 4 yield and 20.2% and 18.9% in CH 4 intensity compared with control for the mode and high dose, respectively.No difference in CH 4 mitigation was observed between the mode and high nitrate dose (Model 2) nor was a linear effect of nitrate dose detected (Model 3).Nitrate supplementation reduced DMI by 0.825 kg/d in Model 1, whereas Model 2 showed that reduction of DMI only occurred at the mode dose (-1.04 kg/d).According to Model 1, nitrate supplementation reduced milk protein yield and content (-0.033 kg/d and -0.087% -units, respectively) and tended to reduce ECM yield (-0.55 kg/d).According to Model 2, nitrate supplementation reduced milk protein content at both mode and high dose (-0.059 and -0.133%-units, respectively), milk protein yield at the mode dose (-0.035 kg/d), and tended to decrease milk protein yield at the high dose (-0.028 kg/d).Furthermore, feed efficiency increased by 3.21% in Model 1 and by 3.59% in Model 2 for the mode dose only.Blood methemoglobin increased upon nitrate supplementation according to Model 1 (+0.695%-units) and Model 2 (high dose only; +1.32% -units) but did not reach levels that posed risks for animal health.In conclusion, the most commonly tested dose of 10 g nitrate/kg DM reduced CH 4 production by 21.5%, CH 4 yield by 15.6% and CH 4 intensity by 20.2%.Dose response analysis indicated no additional reductions when increasing the nitrate dose to a level higher than 10 g/kg DM.Despite the decrease in milk protein content and yield, which was observed at the mode dose of 10 g/kg DM, supplementing nitrate is an effective strategy to reduce CH 4 emission.
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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 | 0.010 | 0.014 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.032 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".