Spatial patterns and driving factor analysis of recommended nitrogen application rate for the trade-off between economy and environment for maize in China-Reference-Cited by-同舟云学术

Spatial patterns and driving factor analysis of recommended nitrogen application rate for the trade-off between economy and environment for maize in China

Published:2022-11 Issue: Volume:322 Page:116099
ISSN:0301-4797
Container-title:Journal of Environmental Management
language:en
Short-container-title:Journal of Environmental Management

Author:

Liu Dantong,Song Changchun,Xin Zhuohang,Fang Chong,Liu Zhihong

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Management, Monitoring, Policy and Law,Waste Management and Disposal,General Medicine,Environmental Engineering

Reference66 articles.

1. Calibration and validation of the DNDC model to estimate nitrous oxide emissions and crop productivity for a summer maize-winter wheat double cropping system in Hebei, China;Abdalla;Environ. Pollut.,2020

2. Using CERES-Maize model to determine the nitrogen fertilization requirements of early maturing maize in the Sudan Savanna of Nigeria;Adnan;J. Plant Nutr.,2017

3. Managing essential plant nutrients to improve maize productivity in the savanna agroecological zones of Northern Ghana: the role of secondary and micronutrients;Agyin-Birikorang;J. Plant Nutr.,2022

4. Optimization of the nitrogen fertilizer schedule of maize under drip irrigation in Jilin, China, based on DSSAT and GA;Bai;Agric. Water Manag.,2021

5. Anion channels/transporters in plants:from molecular bases to regulatory networks;Barbier-Brygoo;Annu. Rev. Plant Biol.,2011

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A fuzzy logic evaluation of synergies and trade-offs between agricultural production and climate change mitigation;Journal of Cleaner Production;2024-01

2. Towards Less Agricultural Nitrogen Use in China: Perspective from a Multi-Crop and Multi-Region Partial Equilibrium Analysis;Polish Journal of Environmental Studies;2023-08-01

3. Optimizing rice in-season nitrogen topdressing by coupling experimental and modeling data with machine learning algorithms;Computers and Electronics in Agriculture;2023-06