Nitrogen Management Trade‐Offs Between Crop Production and Environmental Impact After Long‐Term Conservation Tillage in Northeast China: A <scp>TOPSIS</scp> ‐Based Evaluation
Bibliographic record
Abstract
ABSTRACT Conservation tillage is crucial for rehabilitating degraded cropland, securing crop production and lessening greenhouse gas (GHG) emissions. Yet, the optimal nitrogen (N) application level that balances crop productivity with environmental effects following long‐term conservation tillage remains unclear. Based on a 9‐year conservation tillage experiment of black soil in Northeast China, an in situ microplot experiment was conducted from 2021 to 2023, including six N fertilization levels: 240 (N240, conventional N fertilization level by local farmers), 210 (N210), 180 (N180), 150 (N150), 120 (N120) and 0 kg N ha −1 (N0, control). The systematic effects of N fertilization on crop production, N fertilizer agronomic efficiency (NAE), GHG emissions and N balance were evaluated by using TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution). N fertilization significantly enhanced crop production ( p < 0.05), especially maize grain yield was increased by 27.7%–36.2% in high N fertilization treatments (N180, N210 and N240) over that for N0. The NAE increased with the increase of N fertilization and exhibited a positive nonlinear correlation with the N fertilization level elevating ( R 2 = 0.61), whereas no notable variation in NAE was found across high N fertilization treatments. Moreover, global warming potential (GWP) showed an upward trend with the increase of N fertilization, while greenhouse gas intensity (GHGI) did not show a consistent trend. Analysis of the annual N balance suggested that, except for the N deficit observed in N0. Based on the TOPSIS method, the integrated evaluation showed that N180 ranked first with the total score of 0.61. Overall, from the perspective of crop production, nutrient utilization and the environment, an N fertilization level of 180 kg N ha −1 after long‐term conservation tillage is beneficial for ensuring food security while mitigating global change. This study provided scientific data for optimizing N management and promoting sustainable development of the black soil granary in Northeast China.
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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".