Effects of Manure and Cultivation on Carbon Dioxide and Nitrous Oxide Emissions from a Corn Field under Mediterranean Conditions
Why this work is in the frame
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Bibliographic record
Abstract
The use of organic residues as soil additives is increasing, but, depending on their composition and application methods, these organic amendments can stimulate the emissions of CO(2) and N(2)O. The objective of this study was to quantify the effects of management practices in irrigated sweet corn (Zea mays L.) on CO(2) and N(2)O emissions and to relate emissions to environmental factors. In a 3-yr study, corn residues (CR) and pasteurized chicken manure (PCM) were used as soil amendments compared with no residue (NR) under three management practices: shallow tillage (ST) and no tillage (NT) under consecutive corn crops and ST without crop. Tillage significantly increased (P < 0.05) CO(2) and N(2)O fluxes in residue-amended plots and in NR plots. Carbon dioxide and N(2)O fluxes were correlated with soil NH(4) concentrations and with days since tillage and days since seeding. Fluxes of CO(2) were correlated with soil water content, whereas N(2)O fluxes had higher correlation with air temperature. Annual CO(2) emissions were higher with PCM than with CR and NR (9.7, 2.9, and 2.3 Mg C ha(-1), respectively). Fluxes of N(2)O were 34.4, 0.94, and 0.77 kg N ha(-1) yr(-1) with PCM, CR, and NR, respectively. Annual amounts of CO(2)-C and N(2)O-N emissions from the PCM treatments were 64 and 3% of the applied C and N, respectively. Regardless of cultivation practices, elevated N(2)O emissions were recorded in the PCM treatment. These emissions could negate some of the beneficial effects of PCM on soil properties.
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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 it