Tillage effects on N<sub>2</sub>O emission from soils under corn and soybeans in Eastern Canada
Bibliographic record
Abstract
The ways in which agricultural soils are managed influence the production and emission of nitrous oxide (N 2 O). A field study was undertaken in 2003, 2004, and 2005 to quantify and evaluate N 2 O emission from tilled and no-till soils under corn (Zea maysL.) and soybeans (Glycine max L. Merr) in Ontario. Overall, N 2 O emission was lowest in 2003, the driest and coolest of the 3 yr. In 2004, the significantly larger annual N 2 O emission from no-till soils and soils under corn was attributed to an episode of very high N 2 O emission following the application of fertilizer during a period of wet weather. That the N loss by N 2 O emission occurred only in no-till soils and was large and long-lasting (~4 wk) confirms the strong effect that management has in reducing fertilizer N losses. In 2005, tilled soils had significantly larger N 2 O emission than no-till soils, most of which was emitted before the end of June. Because the tilled soils were better aerated , nitrification was likely the primary process contributing to the larger emission. Relatively low N 2 O emission from soybeans suggests biological N fixation does not appear to contribute substantially to the annual N 2 O emission. Further study of methods to reduce N 2 O emission in agricultural systems should focus on improving N use efficiency within a particular tillage system rather than looking to differences between tillage systems. Key words: Tillage, corn, soybeans, nitrogen, nitrous oxide, biogenic gas emission, nitrification, denitrification, fertilization
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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 | 0.000 | 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 | 0.000 | 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 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".