Growing Season Nitrous Oxide Emissions from a Gray Luvisol as a Function of Long-term Fertilization History and Crop Rotation
Bibliographic record
Abstract
A field study conducted over three growing seasons (2013–2015) assessed the effect of long-term fertilization history and crop rotation on growing season nitrous oxide (N2O) and carbon dioxide (CO2) emissions, wheat yield, wheat N uptake, N2O emission intensity, and soil properties on a Gray Luvisol soil. Long-term fertility treatments included check, manure, NPKS, NPK, and PKS fertilizers in two contrasting crop rotations: 2 yr wheat (Triticum aestivum L.) – fallow (WF), and 5 yr wheat (T. aestivum L.) – oat (Avena sativa) – barley (Hordeum vulgare L.) – alfalfa (Medicago sativa) – brome (Bromus tectorum) hay (WOBHH). Rotation significantly affected cumulative growing season N2O emissions, and within each rotation, long-term fertilizer or manure N additions increased N2O emissions over the check. Average, cumulative growing season N2O emissions in the 5 yr rotation were 1.29 kg N2O-N ha−1, significantly higher than the 0.58 kg N2O-N ha−1 in the WF rotation, but N2O emission intensities were comparable between the two rotations. Cumulative N2O emissions were positively correlated to total soil N (0–15 cm) and wheat N uptake, but N2O emission intensities were negatively correlated to total soil N. However, it is uncertain whether this result extends to annual emission intensities because of a lack of nongrowing season measurements.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".