Effects of encapsulated nitrate on growth performance, carcass characteristics, nitrate residues in tissues, and enteric methane emissions in beef steers: Finishing phase1,2
Bibliographic record
Abstract
A finishing feedlot study was conducted with beef steers to determine effects of encapsulated nitrate (EN) on growth performance, carcass characteristics, methane production, and nitrate (NO) residues in tissues. The 132 crossbred steers were backgrounded in a feedlot for 91 d and transitioned for 28 days to the high-concentrate diets evaluated in the present study, maintaining the treatment and pen assignments designated at the start of the backgrounding period. The steers were initially assigned to 22 pens (6 animals per pen) in a randomized complete block design with BW (18 pens) and animals designated for methane measurement (4 pens) as blocking factors. Five animals in each pen designated for methane measurement (total of 20 animals) were monitored for methane emissions in respiratory chambers twice during the experiment. Pens received 3 dietary treatments (7 pens each): Control, a finishing diet supplemented with urea; 1.25% EN, control diet supplemented with 1.25% encapsulated NO in dietary DM that partially replaced urea; and 2.5% EN, control diet supplemented with 2.5% EN (DM basis) fully replacing urea. The final pen designated only for methane measurement received a fourth dietary treatment, 2.3% UEN, the control diet supplemented with unencapsulated NO (UEN) fully replacing urea. The cattle weighed 449 ± SD 32 kg at the start of the 150-d finishing period. The 2.5% EN diet decreased ( < 0.01) DMI compared with Control and 1.25% EN diets. Feeding EN tended to increase ( = 0.092) ADG compared with Control, and G:F was improved ( < 0.01) for EN compared with Control. No differences in methane production (g/d) and yield (g/kg DMI) were observed among treatments. Inclusion of EN in the diets increased ( ≤ 0.03) sorting in favor of large and medium particles and against small and fine particles. Plasma NO and NO concentrations were elevated ( < 0.01) with EN in a dose-response manner, but total blood methemoglobin levels for all treatments were low, below the detection limit. Feeding EN increased ( < 0.01) NO concentrations of samples from muscle, fat, liver, and kidney; NO concentrations of these tissues were similar between 1.25% EN and 2.3% UEN. In conclusion, inclusion of 2.5% EN in a finishing diet (DM basis; about 2% NO) did not cause NO toxicity or any health problems in the long term. In comparison with supplemental urea, feeding EN improved feed efficiency despite increases in sorting against dietary EN.
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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 | 0.001 |
| 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 | 0.001 |
| 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".