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Journal of Integrative Agriculture  2022, Vol. 21 Issue (12): 3637-3657    DOI: 10.1016/j.jia.2022.08.054
Special Issue: 农业生态环境-氮素合辑Agro-ecosystem & Environment—Nitrogen
Agro-ecosystem & Environment Advanced Online Publication | Current Issue | Archive | Adv Search |
Statistical analysis of nitrogen use efficiency in Northeast China using multiple linear regression and random forest
LIU Ying-xia1, 2, 3, Gerard B. M. HEUVELINK2, 3, Zhanguo BAI3, HE Ping1, JIANG Rong1, HUANG Shao-hui1, XU Xin-peng1

1 Key Laboratory of Plant Nutrition and Fertilizer, Ministry of Agriculture and Rural Affairs/Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, P.R.China

2 Soil Geography and Landscape Group, Wageningen University, Wageningen 6700 AA, The Netherlands

3 International Soil Reference and Information Centre - World Soil Information, Wageningen 6700 AJ, The Netherlands

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Understanding the spatial-temporal dynamics of crop nitrogen (N) use efficiency (NUE) and the relationship with explanatory environmental variables can support land-use management and policymaking.  Nevertheless, the application of statistical models for evaluating the explanatory variables of space-time variation in crop NUE is still under-researched.  In this study, stepwise multiple linear regression (SMLR) and Random Forest (RF) were used to evaluate the spatial and temporal variation of NUE indicators (i.e., partial factor productivity of N (PFPN); partial nutrient balance of N (PNBN)) at county scale in Northeast China (Heilongjiang, Liaoning and Jilin provinces) from 1990 to 2015.  Explanatory variables included agricultural management practices, topography, climate, economy, soil and crop types.  Results revealed that the PFPN was higher in the northern parts and lower in the center of the Northeast China and PNBN increased from southern to northern parts during the 1990–2015 period.  The NUE indicators decreased with time in most counties during the study period.  The model efficiency coefficients of the SMLR and RF models were 0.44 and 0.84 for PFPN, and 0.67 and 0.89 for PNBN, respectively.  The RF model had higher relative importance of soil and climatic covariates and lower relative importance of crop covariates compared to the SMLR model.  The planting area index of vegetables and beans, soil clay content, saturated water content, enhanced vegetation index in November & December, soil bulk density, and annual minimum temperature were the main explanatory variables for both NUE indicators.  This is the first study to show the quantitative relative importance of explanatory variables for NUE at a county level in Northeast China using RF and SMLR.  This novel study gives reference measurements to improve crop NUE which is one of the most effective means of managing N for sustainable development, ensuring food security, alleviating environmental degradation and increasing farmer’s profitability.

Keywords:  partial factor productivity of N        partial nutrient balance of N       stepwise multiple linear regression       random forest       county scale       Northeast China  
Received: 01 September 2021   Accepted: 03 December 2021

We are specially acknowledgeable financial support from the China Scholarship Council (CSC) (201903250115).  This research was supported by the National Natural Science Foundation of China (31972515) and the China Agriculture Research System of MOF and MARA (CARS–09-P31).

About author:  LIU Ying-xia, E-mail:; Correspondence HE Ping, Tel: +86-10-82105638, E-mail:

Cite this article: 

LIU Ying-xia, Gerard B. M. HEUVELINK, Zhanguo BAI, HE Ping, JIANG Rong, HUANG Shao-hui, XU Xin-peng. 2022. Statistical analysis of nitrogen use efficiency in Northeast China using multiple linear regression and random forest. Journal of Integrative Agriculture, 21(12): 3637-3657.

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