Feeding sunflower oil to partially defaunate the rumen increases nitrogen retention, urea-nitrogen recycling to the gastrointestinal tract and the anabolic use of recycled urea-nitrogen in growing lambs
Bibliographic record
Abstract
The objective of the present study was to delineate how interactions between feeding sunflower oil (SFO) to partially defaunate the rumen and altering dietary ruminally fermentable carbohydrate may alter urea-N kinetics and N metabolism in lambs. In a 4 × 4 Latin square with a 2 × 2 factorial arrangement of treatments, four Suffolk ram lambs (61·5 (se 4·0) kg) were used. Treatments were 0 ( - SFO) v. 6 % (+SFO) SFO and dry-rolled barley (DRB) v. pelleted barley (PB). N balance was measured over 4 d, with concurrent measurement of urea-N kinetics using continuous intra-jugular infusions of [(15)N(15)N]urea. Feeding SFO decreased (P = 0·001) ruminal protozoa and NH3-N concentrations. Urinary N excretion was lower (P = 0·003), and retained N was higher (P = 0·002) in +SFO lambs compared with - SFO lambs. Endogenous production of urea-N (urea-N entry rate; UER) was similar across treatments. Urea-N transfer to the gastrointestinal tract (GIT) (GIT entry rate; GER), expressed as absolute amounts (16·4 v. 13·1 g/d) or as a proportion of the UER (0·693 v. 0·570), its anabolic use (9·0 v. 6·0 g/d) and microbial N supply (14·6 v. 10·9 g/d) were higher (P ≤ 0·001) in +SFO lambs compared with -SFO lambs. As a proportion of the UER, GER was higher, whereas urinary urea-N loss was lower, in lambs fed PB compared with those fed DRB (P = 0·01). In summary, feeding SFO increased urea-N recycling to the GIT and microbial non-NH(3)-N supply, thus providing new evidence that the improved efficiency of N utilization in partially defaunated ruminants could be partly mediated by an increase in urea-N recycling.
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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 | 0.000 | 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 | 0.000 |
| 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".