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

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) con...

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Autores principales: Yao, Bo, Wang, Xiaolong, Wang, Yancheng, Ye, Tianyang, Wang, Enli, Cao, Qiang, Yao, Xia, Zhu, Yan, Cao, Weixing, Liu, Xiaojun, Tang, Liang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AAAS 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10396079/
https://www.ncbi.nlm.nih.gov/pubmed/37539074
http://dx.doi.org/10.34133/plantphenomics.0078
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author Yao, Bo
Wang, Xiaolong
Wang, Yancheng
Ye, Tianyang
Wang, Enli
Cao, Qiang
Yao, Xia
Zhu, Yan
Cao, Weixing
Liu, Xiaojun
Tang, Liang
author_facet Yao, Bo
Wang, Xiaolong
Wang, Yancheng
Ye, Tianyang
Wang, Enli
Cao, Qiang
Yao, Xia
Zhu, Yan
Cao, Weixing
Liu, Xiaojun
Tang, Liang
author_sort Yao, Bo
collection PubMed
description 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.
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spelling pubmed-103960792023-08-03 Interaction of Genotype, Environment, and Management on Organ-Specific Critical Nitrogen Dilution Curve in Wheat Yao, Bo Wang, Xiaolong Wang, Yancheng Ye, Tianyang Wang, Enli Cao, Qiang Yao, Xia Zhu, Yan Cao, Weixing Liu, Xiaojun Tang, Liang Plant Phenomics Research Article 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. AAAS 2023-08-02 /pmc/articles/PMC10396079/ /pubmed/37539074 http://dx.doi.org/10.34133/plantphenomics.0078 Text en Copyright © 2023 Bo Yao et al. https://creativecommons.org/licenses/by/4.0/Exclusive licensee Nanjing Agricultural University. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution License 4.0 (CC BY 4.0) (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Research Article
Yao, Bo
Wang, Xiaolong
Wang, Yancheng
Ye, Tianyang
Wang, Enli
Cao, Qiang
Yao, Xia
Zhu, Yan
Cao, Weixing
Liu, Xiaojun
Tang, Liang
Interaction of Genotype, Environment, and Management on Organ-Specific Critical Nitrogen Dilution Curve in Wheat
title Interaction of Genotype, Environment, and Management on Organ-Specific Critical Nitrogen Dilution Curve in Wheat
title_full Interaction of Genotype, Environment, and Management on Organ-Specific Critical Nitrogen Dilution Curve in Wheat
title_fullStr Interaction of Genotype, Environment, and Management on Organ-Specific Critical Nitrogen Dilution Curve in Wheat
title_full_unstemmed Interaction of Genotype, Environment, and Management on Organ-Specific Critical Nitrogen Dilution Curve in Wheat
title_short Interaction of Genotype, Environment, and Management on Organ-Specific Critical Nitrogen Dilution Curve in Wheat
title_sort interaction of genotype, environment, and management on organ-specific critical nitrogen dilution curve in wheat
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10396079/
https://www.ncbi.nlm.nih.gov/pubmed/37539074
http://dx.doi.org/10.34133/plantphenomics.0078
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