The effects of feeding 3-nitrooxypropanol on methane emissions and productivity of Holstein cows in mid lactation
Bibliographic record
Abstract
The objective of the current study was to determine the effects of adding 3-nitrooxypropanol to the diet of lactating Holstein cows on methane emissions, rumen fermentation, ruminal microbial profile, and milk production. Twelve ruminally cannulated Holstein cows in midlactation were used in a crossover design study with 28-d periods. Cows were fed a diet containing 38% forage on a dry matter basis with either 2,500 mg/d of 3-nitrooxypropanol (fed as 25 g of 10% 3-nitrooxypropanol on silicon dioxide) or 25 g/d of silicon dioxide (control). After a 21-d diet adaptation period, dry matter intake (DMI) and milk yield were recorded daily. Rumen fluid and digesta were collected on d 22 and 28 for volatile fatty acid analysis and microbial profiling. Enteric methane emissions were measured on d 23 to 27 using the sulfur hexafluoride tracer gas technique. Feeding 3-nitrooxypropanol did not affect DMI; however, methane production was reduced from 17.8 to 7.18 g/kg of DMI. No change in milk or milk component yields was observed, but cows fed 3-nitrooxypropanol gained more body weight than control cows (1.06 vs. 0.39 kg/d). Concentrations of total volatile fatty acids in ruminal fluid were not affected by treatment, but a reduction in acetate proportion and a tendency for an increase in propionate proportion was noted. As such, a reduction in the acetate-to-propionate ratio was observed (2.02 vs. 2.36). Protozoa counts were not affected by treatment; however, a reduction in methanogen copy count number was observed when 3-nitrooxypropanol was fed (0.95 vs. 2.69 × 10(8)/g of rumen digesta). The data showed that feeding 3-nitrooxypropanol to lactating dairy cows at 2,500 mg/d can reduce methane emissions without compromising DMI or milk production.
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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 | 0.002 |
| 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) | 0.000 | 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".