N<sub>2</sub>O emissions from spring barley production as influenced by fertilizer nitrogen rate
Bibliographic record
Abstract
Usage of mineral nitrogen (N) fertilizers for agricultural crop production systems is a major contributor to anthropogenic nitrous oxide (N 2 O) emissions. As part of a national study to quantify N 2 O emissions under different cropping systems and in different eco-regions, this study quantified the effect of fertilizer N rate on spring barley (Hordeum vulgare L.) on N 2 O emissions in 3 yr in a cool maritime climate with humid soil moisture regimes. Treatments were 0, 75 and 150 kg N ha -1 as ammonium nitrate applied as a pre-plant broadcast. N 2 O emissions were increased by fertilizer N application in each year. In 2003 and 2005, elevated N 2 O emissions occurred in the 6-wk period following fertilizer application when soil NO 3 -N concentrations were high. However, in 2004 and 2005, peak N 2 O emissions occurred near crop harvest. Elevated N 2 O emissions at this time were attributed to increased carbon availability due to re-wetting of dry soil. Therefore, the effect of fertilizer N management on N 2 O emissions may not necessarily occur immediately after treatment application. This emphasizes the importance of measuring N 2 O emissions outside of the crop growth period. Fertilizer-induced cumulative N 2 O emissions averaged 0.011 and 0.021 kg N kg -1 N when fertilizer N rate was increased from 0 to 75 kg N ha -1 and from 75 to 150 kg N ha -1 , respectively, indicating increased N 2 O emissions when fertilizer is applied at above optimal rates. N 2 O emissions increased linearly with nitrate intensity, the summation of daily NO 3 -N concentrations for 0- to 15-cm depth. This suggests that the non-linearity in the relationship between fertilizer N rate and N 2 O emissions can be explained by the decreasing efficiency in crop NO 3 -N uptake at high fertilizer N rates. Key words: Hordeum vulgare, soil nitrate, denitrification, carbon availability
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".