Fertilizer Source Influenced Nitrous Oxide Emissions from a Clay Soil under Corn
Bibliographic record
Abstract
Synthetic N fertilizers are a major source of N 2 O emissions from soil. A field experiment was conducted during three growing seasons (2004–2006) on a clay soil (fine, mixed, frigid Typic Humaquept) under corn ( Zea mays L.) to evaluate the impact of N fertilizer source and application rate on N 2 O emissions. Treatments consisted of three sources of N fertilizer (urea–NH 4 NO 3 32% [UAN], Ca–NH 4 NO 3 [CAN], and aqua NH 3 [AA]) at four different rates (0, 100, 150, and 200 kg N ha −1 ). Fertilizers were banded 5 cm below the soil surface between corn rows at the six‐leaf stage and N 2 O emissions were measured weekly. For all 3 yr of this study, cumulative N 2 O emission decreased in the order UAN ≥ CAN ≥ AA. Averaged across years, fertilizer‐induced post‐sidedress emissions were greater than the Intergovernmental Panel on Climate Change default factor (0.01 kg N 2 O‐N kg −1 N), with values of 0.038, 0.033, and 0.027 kg N 2 O‐N kg −1 N for UAN, CAN, and AA, respectively. The N 2 O emissions increased linearly with N rate, even at rates exceeding the optimum level for grain yield. Peaks of N 2 O flux occurred on the days following fertilizer application and in early fall when the soil was re‐wetted. Emissions of N 2 O were higher at water‐filled pore space >0.57 m 3 m −3 and were also related to soil inorganic N and water‐extractable organic C contents. Our results confirm that N fertilizer source and application rate can impact N 2 O emissions but these effects are modulated by soil environmental conditions.
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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 | 0.000 | 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".