Interaction of Genotype, Environment, and Management on Organ-Specific Critical Nitrogen Dilution Curve in Wheat

Author:

Yao Bo1ORCID,Wang Xiaolong1,Wang Yancheng1,Ye Tianyang1,Wang Enli2,Cao Qiang1,Yao Xia1,Zhu Yan1,Cao Weixing1,Liu Xiaojun1,Tang Liang1ORCID

Affiliation:

1. National Engineering and Technology Center for Information Agriculture, Engineering Research Center for Smart Agriculture, Ministry of Education, Key Laboratory for Crop System Analysis and Decision Making, Ministry of Agriculture and Rural Affairs, Jiangsu Key Laboratory for Information Agriculture, Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing 210095, Jiangsu, PR China.

2. CSIRO Agriculture and Food, Cluniess Ross Street, Black Mountain, ACT, Australia.

Abstract

The organ-specific critical nitrogen (N c ) dilution curves are widely thought to represent a new approach for crop nitrogen (N) nutrition diagnosis, N management, and crop modeling. The N c dilution curve can be described by a power function (N c = A 1 ·W −A2 ), while parameters A 1 and A 2 control the starting point and slope. This study aimed to investigate the uncertainty and drivers of organ-specific curves under different conditions. By using hierarchical Bayesian theory, parameters A 1 and A 2 of the organ-specific N c dilution curves for wheat were derived and evaluated under 14 different genotype × environment × management (G × E × M) N fertilizer experiments. Our results show that parameters A 1 and A 2 are highly correlated. Although the variation of parameter A 1 was less than that of A 2 , the values of both parameters can change significantly in response to G × E × M. Nitrogen nutrition index (NNI) calculated using organ-specific N c is in general consistent with NNI estimated with overall shoot N c , indicating that a simple organ-specific N c dilution curve may be used for wheat N diagnosis to assist N management. However, the significant differences in organ-specific N c dilution curves across G × E × M conditions imply potential errors in N c and crop N demand estimated using a general N c dilution curve in crop models, highlighting a clear need for improvement in N c calculations in such models. Our results provide new insights into how to improve modeling of crop nitrogen–biomass relations and N management practices under G × E × M.

Publisher

American Association for the Advancement of Science (AAAS)

Subject

Agronomy and Crop Science

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