Effects of Feeding Encapsulated Nitrate to Beef Cattle on Ammonia and Greenhouse Gas Emissions from Their Manure in a Short‐Term Manure Storage System
Bibliographic record
Abstract
A study was conducted to investigate effects of feeding encapsulated nitrate (EN) to beef cattle on ammonia (NH) and greenhouse gas emissions from their manure. Eight beef heifers were randomly assigned to diets containing 0 (control), 1, 2, or 3% EN (55% forage dry matter; EN replaced encapsulated urea in the control diet and therefore all diets were iso-nitrogenous) in a replicated 4 × 4 Latin square design. Urine and feces collected from individual animals were reconstituted into manure and incubated over 156 h using a steady-state flux chamber system to monitor NH, methane (CH), carbon dioxide (CO), and nitrous oxide (NO) emissions. Urinary, fecal, and manure nitrate (NO)-N concentration linearly increased ( < 0.001) with feeding EN, and urinary urea concentration tended to be lower ( = 0.078) for EN versus Control. The hourly emissions of NH, CO, and NO (mg head h) were not affected, although NH emission rates tended to be lower ( = 0.070) for EN compared with Control at 0 to 12 h. Cumulative NH, CO, and NO emissions over 156 h were not affected, but CH emissions were less (4.5 vs. 7.4 g head; = 0.027) for EN compared with Control. In conclusion, although NH emissions were initially lower for EN manures, total NH emitted over 156 h was not affected. Dietary EN lowered CH emissions from manure, and, despite greater NO concentrations in EN manure, NO emissions were not affected in this short-term incubation.
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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 | 0.001 |
| 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".