Ammonia volatilization and soil nitrogen dynamics following fall application of pig slurry on canola crop residues
Bibliographic record
Abstract
Land application of liquid manures is a major source of atmospheric ammonia. The presence of crop residues on the soil surface usually increases emissions by retarding slurry infiltration, whereas incorporation of slurry into soil reduces emissions. Our objective was to quantify the relative reduction in NH3 volatilization resulting from the soil incorporation of pig slurry (PS) applied on canola (Brassica napus) residues under fall conditions in Quebec, Canada. Pig slurry was applied at 7.4 L m–2 on six plots covered by canola crop residues. Slurry and residues were incorporated in the top 5 cm of soil (INCORP) in half of the plots, while the other half were left untouched (SURF). Ammonia volatilization was measured following application for 10 d using wind tunnels. Soil NH4+ and NO3− contents, pH, moisture and temperature were also monitored to explain variations in NH3 fluxes. Soil NH4+-N in the surface soil was lower than expected shortly after slurry application, maybe as a result of fixation by clays or interception by crop residues. The volatilization of NH3 was higher (P < 0.05) on SURF plots than on INCORP plots in 20 of the 26 measuring periods, with total NH3 losses being five times greater in the former. Cumulated emissions during the first 11 h accounted for the 60 and 53% of total NH3 emissions for the SURF and INCORP plots, respectively. Our results confirm that a large fraction of the NH3 volatilization from slurry application on canola residues can be greatly reduced if the slurry and crop residues are incorporated into the soil immediately after slurry application. Despite significant reduction (80%) of NH3 volatilization in INCORP compared with SURF plots, no difference was found in soil mineral N between treatments, suggesting that other processes such as N mineralization or denitrification were more active in INCORP plots. Key Words: Ammonium, nitrate, nitrogen cycle, organic amendments
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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) | 0.001 | 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".