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Record W4416772439 · doi:10.1002/ldr.70338

Nitrogen Management Trade‐Offs Between Crop Production and Environmental Impact After Long‐Term Conservation Tillage in Northeast China: A <scp>TOPSIS</scp> ‐Based Evaluation

2025· article· en· W4416772439 on OpenAlexaff
Yang Zhang, Yan Zhang, Yan Gao, Neil B. McLaughlin, Chenchen Lou, Xuewen Chen, Dandan Huang, Jinyu Zheng, Aizhen Liang, Christoph Müller

Bibliographic record

VenueLand Degradation and Development · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoil Carbon and Nitrogen Dynamics
Canadian institutionsAgriculture and Agri-Food Canada
FundersNational Key Research and Development Program of ChinaPeople's Government of Jilin ProvinceChina Postdoctoral Science FoundationNational Natural Science Foundation of China
KeywordsTillageHuman fertilizationConventional tillageGreenhouse gasCrop yieldCropFertilizerGreenhouseMinimum tillage

Abstract

fetched live from OpenAlex

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 &lt; 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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.079
Threshold uncertainty score0.304

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.014
GPT teacher head0.237
Teacher spread0.223 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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