Nitrous oxide emissions as affected by liquid and solid pig manures applied to annual and perennial forage crops on a sandy loam soil
Bibliographic record
Abstract
Emissions of nitrous oxide (N2O-N) from manure applied to annual crop (AC) and perennial forage (PF) are poorly quantified for the Canadian Prairie Region. This study used static chambers over two growing seasons to assess soil N2O-N emissions from solid pig manure (SPM) and liquid pig manure (LPM) in AC and PF systems on a sandy loam soil. In 2011, when manure application coincided with hot and wet soil conditions, both manure treatments in AC induced N2O-N emission episodes a week later. In the PF, however, only LPM resulted in an N2O-N emission peak after 8 d. In 2012, manure application did not coincide with hot and wet soil conditions, and emission rates were smaller. Overall, the effect of manure type was inconsistent. In 2011, cumulative emissions in AC from LPM and SPM were 5.8 and 7.8 kg N2O-N ha−1, respectively, and in PF were 10.7 and 0.6 kg N2O-N ha−1, respectively. In 2012, cumulative emissions were <1 kg N2O-N ha−1, except LPM in PF. In 2011, LPM had significantly higher emission factor (EF ≍ 7%) than SPM (≤0.2%) in both AC and PF, whereas in 2012 manure type had no effect on EF (≍ 0). Over the two growing seasons and across manure types, EF did not differ between AC and PF. These results suggest that SPM would reduce N2O-N emission relative to LPM when conditions favor intense denitrification.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".