Short-Term Assessment of Nitrous Oxide and Methane Emissions on a Crop Yield Basis in Response to Different Organic Amendment Types in Sichuan Basin
Bibliographic record
Abstract
Agriculture’s goal to meet the needs of the increasing world population while reducing the environmental impacts of nitrogen (N) fertilizer use without compromising output has proven to be a challenge. Manure and composts have displayed the potential to increase soil fertility. However, their potential effects on nitrous oxide (N2O) and methane (CH4) emissions have not been properly understood. Using field-scaled lysimeter experiments, we conducted a one-year study to investigate N2O and CH4 emissions, their combined global warming potential (GWP: N2O + CH4) and yield-scaled GWP in a wheat-maize system. One control and six different organic fertilizer treatments receiving different types but equal amounts of N fertilization were used: synthetic N fertilizer (NPK), 30% pig manure + 70% synthetic N fertilizer (PM30), 50% pig manure + 50% synthetic N fertilizer (PM50), 70% pig manure + 30% synthetic N fertilizer (PM70), 100% pig manure (PM100), 50% cow manure-crop residue compost + 50% synthetic N fertilizer (CMRC), and 50% pig manure-crop residue compost + 50% synthetic N fertilizer (PMRC). Seasonal cumulative N2O emissions ranged from 0.39 kg N ha−1 for the PMRC treatment to 0.93 kg N ha−1 for the NPK treatment. Similar CH4 uptakes were recorded across all treatments, with values ranging from −0.68 kg C ha−1 for the PM50 treatment to −0.52 kg C ha−1 for the PM30 treatment. Compared to the NPK treatment, all the organic-amended treatments significantly decreased N2O emission by 32–58% and GWP by 30–61%. However, among the manure-amended treatments, only treatments that consisted of inorganic N with lower or equal proportions of organic manure N treatments were found to reduce N2O emissions while maintaining crop yields at high levels. Moreover, of all the organic-amended treatments, PMRC had the lowest yield-scaled GWP, owing to its ability to significantly reduce N2O emissions while maintaining high crop yields, highlighting it as the most suitable organic fertilization treatment in Sichuan basin wheat-maize systems.
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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".