Yao Bo, Wang Xiaolong, Wang Yancheng, Ye Tianyang, Wang Enli, Cao Qiang, Yao Xia, Zhu Yan, Cao Weixing, Liu Xiaojun, Tang Liang
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.
CSIRO Agriculture and Food, Cluniess Ross Street, Black Mountain, ACT, Australia.
Plant Phenomics. 2023 Aug 2;5:0078. doi: 10.34133/plantphenomics.0078. eCollection 2023.
The organ-specific critical nitrogen (N) dilution curves are widely thought to represent a new approach for crop nitrogen (N) nutrition diagnosis, N management, and crop modeling. The N dilution curve can be described by a power function (N = A·W), while parameters A and A 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 and A of the organ-specific N 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 and A are highly correlated. Although the variation of parameter A was less than that of A, the values of both parameters can change significantly in response to G × E × M. Nitrogen nutrition index (NNI) calculated using organ-specific N is in general consistent with NNI estimated with overall shoot N, indicating that a simple organ-specific N dilution curve may be used for wheat N diagnosis to assist N management. However, the significant differences in organ-specific N dilution curves across G × E × M conditions imply potential errors in N and crop N demand estimated using a general N dilution curve in crop models, highlighting a clear need for improvement in N 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.
器官特异性临界氮（N）稀释曲线被广泛认为是一种用于作物氮（N）营养诊断、氮管理和作物建模的新方法。氮稀释曲线可以用幂函数（N = A·W）来描述，其中参数A和A控制着起点和斜率。本研究旨在探究不同条件下器官特异性曲线的不确定性及其驱动因素。通过使用分层贝叶斯理论，在14个不同基因型×环境×管理（G×E×M）氮肥试验中推导并评估了小麦器官特异性氮稀释曲线的参数A和A。我们的结果表明，参数A和A高度相关。虽然参数A的变化小于参数A，但这两个参数的值都会因G×E×M而发生显著变化。利用器官特异性氮计算的氮营养指数（NNI）总体上与用地上部总氮估算的NNI一致，这表明简单的器官特异性氮稀释曲线可用于小麦氮诊断以辅助氮管理。然而，不同G×E×M条件下器官特异性氮稀释曲线的显著差异意味着在作物模型中使用通用氮稀释曲线估算氮和作物氮需求时可能存在潜在误差，这突出表明此类模型中的氮计算有明显的改进需求。我们的结果为如何在G×E×M条件下改进作物氮-生物量关系建模和氮管理实践提供了新的见解。
