Nitrous oxide fluxes from corn fields: on‐farm assessment of the amount and timing of nitrogen fertilizer
Bibliographic record
Abstract
Abstract Nitrogen fertilization is considered as an important source of atmospheric N 2 O emission. A seven site‐year on‐farm field experiment was conducted at Ottawa and Guelph, ON and Saint‐Valentin, QC, Canada to characterize the affect of the amount and timing of N fertilizer on N 2 O emission in corn ( Zea mays L.) production. Using the static chamber method, gas samples were collected for 28‐days after preplant and 28‐days after sidedress fertilization at the seven site‐year, resulting in 14 monitoring periods. For both methods of fertilization, peak N 2 O flux and cumulative emission increased with the amount of N applied, with rates ranging from 30 to 900 μg N m −2 h −1 . Depending on N amount and time of application, cumulative emission varied from 0.05 to 2.42 kg N ha −1 , equivalent to 0.03% to 1.45% of the N fertilizer applied. Differences in N 2 O emission peaks among fertilizer treatments were clearly separated in 13 out of 14 monitoring periods. Total N 2 O emissions may have been underestimated compared with annual monitoring in 10 out of the 49 cases because the monitoring period ended before N 2 O efflux returned to the baseline level. The flux of N 2 O was negligible when soil mineral N in the 0–15 cm layer was < 20 mg N kg −1 . While rainfall stimulated emission, soil temperature > 15 °C was likely the driving force responsible for the higher levels of N 2 O found for sidedress than preplant application methods. However, caution must be taken when interpreting these later results as preplant fertilization may have continuously stimulated N 2 O emissions after the 28‐days monitoring period, especially in situations where N 2 O effluxes have not fallen back to their baseline levels. Increasing fertilizer rates from 90 to 150 kg N ha −1 resulted in slight increases in yields, but doubled cumulative N 2 O emissions.
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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".