The effects of feeding 3-nitrooxypropanol at two doses on milk production, rumen fermentation, plasma metabolites, nutrient digestibility, and methane emissions in lactating Holstein cows
Bibliographic record
Abstract
The objective of this study was to determine the effects of feeding 3-nitrooxypropanol (NOP) in the total mixed ration of lactating Holstein cows on rumen fermentation, ruminal microbial population, enteric methane production, milk production, nutrient digestibility, and blood metabolites. Fifteen ruminally cannulated Holstein cows in mid to late lactation were used in a 3 × 3 Latin square design study with 28-day periods. Cows were fed a 60%-forage diet (dry matter basis) with 2500 (HIGH), 1250 (LOW) or 0 (CON) mg/day of NOP. After a 20-day diet adaptation period, dry matter intake (DMI) and milk yield were recorded daily. Rumen digesta and rumen fluid were collected on Days 21 and 28 and ruminal pH was determined on Days 23–28. Methane emissions were measured on Days 23–27 using the sulfur hexafluoride tracer gas technique. Faecal and blood samples were taken on Days 25–27. Feeding NOP at either dose did not affect DMI, milk production or bodyweight gain. Total concentration of volatile fatty acids in rumen fluid did not differ; however, there was a decrease in molar proportion of acetate and increase in molar proportion of propionate with feeding NOP in a dose-dependent manner. Microbial profile and ruminal pH were not affected by treatment. Apparent total-tract digestibility of DM (62.7% vs 58.4%; P < 0.05) and neutral detergent fibre (38.0% vs 30.7%; P < 0.05) were increased with the HIGH dose compared with CON. Feeding NOP reduced methane yield from 19.9 to 15.3 g/kg DMI for CON versus LOW (P < 0.05) and from 19.9 to 12.6 for CON versus HIGH (P < 0.05). Feeding NOP at 1250 or 2500 mg/day reduced methane yield and affected ruminal volatile fatty acid profile without compromising DMI or apparent total-tract nutrient digestibility.
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.
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) | 0.001 | 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 | 0.001 |
| 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".