Effects of Manure and Cultivation on Carbon Dioxide and Nitrous Oxide Emissions from a Corn Field under Mediterranean Conditions
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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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".