Effects of Fertilizers and Mushroom Residues on Soil N2O Emission Under Rice-Wheat Rotation in Chengdu Plain
Bibliographic record
Abstract
Nitrous oxide (N2O) is a greenhouse gas, and agricultural landscapes are major sources of atmospheric N2O. In this study, different types and levels of fertilization were applied to rice and wheat plants, including full crop straw, pure synthetic fertilizer and spent agro-residues from mushroom cultivation. N2O flux measurements were performed once a week using gas static chromatography-chamber between 2008 and 2009. In order to find out the effect of MR application on N2O emission, soil samples, environment-monitoring factors including soil moisture and temperature and biomass were also determined. Soil nitrate and ammonia were measured in soil extracts. The results showed that the total N2O emission decreased to 19,066 kg ha-1 in the rice stage and 45,312 kg ha-1 in the wheat stage under the mushroom residue (MR) application. This observation indicated that MR application (22,656.40 kg for rice and 9,533.33 kg for wheat) induced a decrease of N2O emission by 62.52% and 67.55% as compared with fertilizer and straw application, which are 6328.77±740.81b g ha-1, 7310.60±279.73b g ha-1 respectively. Therefore, MR application could be one of the most effective ways to reduce soil N2O emissions.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".