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Updated: Aug 22, 2025

Microplot Design and Plant and Soil Sample Preparation for 15Nitrogen Analysis
Published on: May 10, 2020
Driving forces of nitrogen use efficiency in Chinese croplands on county scale
Binhui Chen1, Chenchen Ren2, Chen Wang1
1College of Environmental & Resource Sciences, Zhejiang University, Hangzhou, 310058, China; Policy Simulation Laboratory, Zhejiang University, Hangzhou, 310058, China.
Abstract:
Nitrogen use efficiency (NUE, defined as the fraction of N input harvested as product) is an important indicator to understand nitrogen use and losses in croplands as an element of determining sustainable food production. China, as the country with the largest amount of nitrogen fertilizer use globally, research into NUE consistently finds it to be much lower than that in developed countries. Understanding the driving forces of the underlying causes of this low NUE is thus crucial to improve nitrogen use and reduce losses in China. Here we applied the CHANS model to estimate cropland NUE for over 2800 counties in China for the year 2017. Results showed that in most counties NUE ranged between 20% and 40%, while an NUE >50% was mainly found in Northeastern China, likely as a result of large-scale, modern agriculture operations. The source of N input and crop types significantly affected NUE in our assessment. Nitrogen deposition, straw recycling, and biological nitrogen fixation (BNF) could improve NUE, while chemical nitrogen fertilizer and manure inputs reduce NUE. Grain crops have a much higher NUE compared to vegetables, which are often over-fertilized. Moreover, NUE in Southern China is strongly influenced by natural factors such as temperature and precipitation. Specifically, NUE in the Yangtze River Delta (eastern coastal region of China) is associated with socio-economic factors including GDP and the degree of urbanization, while in North-central China, NUE is mainly determined by nitrogen input sources. These examples illustrate that approaches aiming at improving NUE need to be location-specific with consideration of multiple natural and socioeconomic factors.
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