Effect of fertilizer nitrogen management on N<sub>2</sub>O emissions in commercial corn fields
Bibliographic record
Abstract
This study examined the effect of rate and time of fertilizer N application to corn on N2O emissions in 2 yr on commercial corn fields. All treatments received starter fertilizer at 45 and 59 kg N ha-1 in 2004 and 2005, respectively, similar to grower practice. Treatments included a control, with no additional fertilizer N application, 75 or 150 kg N ha-1 banded at sidedress or 150 kg N ha-1 broadcast at emergence. There was no significant effect of N fertility treatment on corn grain or silage yield, indicating that all N applications were at or in excess of crop N requirement. Delay of fertilizer application to sidedress and reduced fertil izer N application were effective in reducing nitrate intensity, an index of soil nitrate availability calculated as the summation of daily soil NO3−-N concentration for the 0- to 15-cm depth. However, there was no significant effect of N fertility treatment on cumulative N2O emissions, and nitrate intensity explained a small proportion of the variation in cumulative N2O emissions. This study provides evidence that improved fertilizer N management may not result in reduced N2O emissions under some conditions. Key words: Zea mays, nitrate, denitrification, carbon availability, soil aeration
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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) | 0.000 | 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 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".