Spatial Patterns of Relationship Between Wheat Yield and Yield Components in China

Yang, X; McMaster, GS; Yu, Q

Spatial Patterns of Relationship Between Wheat Yield and Yield Components in China

Yang, X McMaster, GS Yu, Q

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Publication Type:: Journal Article
Citation:: International Journal of Plant Production, 2018, 12 (1), pp. 61 - 71
Issue Date:: 2018-03-01

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Field	Value	Language
dc.contributor.author	Yang, X	en_US
dc.contributor.author	McMaster, GS	en_US
dc.contributor.author	Yu, Q https://orcid.org/0000-0001-6950-1821	en_US
dc.date.issued	2018-03-01	en_US
dc.identifier.citation	International Journal of Plant Production, 2018, 12 (1), pp. 61 - 71	en_US
dc.identifier.issn	1735-6814	en_US
dc.identifier.uri	http://hdl.handle.net/10453/131009
dc.description.abstract	© 2018, Springer International Publishing AG, part of Springer Nature. The considerable plasticity of wheat (Triticum aestivum L.) in reaching final yield is dynamically determined by three yield components: spike number m−2 (SN), kernel number spike−1 (KN) and 1000-kernel weight (KW). Understanding the contribution of yield components to the variation of grain yield under different production environments is essential for designing breeding programs and increasing grain production. This study analyzed 2 years of experimental data from the Chinese Variety Evaluation Program to explore the relationship between grain yield and yield components in four main winter wheat production regions. Correlation and path analysis were the main methods used in this paper. Yield and yield components were restricted by high temperature and lower sunshine hours at southern regions (Upper Yangtze Valleys, UY and Middle and Lower Yangtze Valleys, MLY). No relationship between yield and climate elements was found at northern region (Yellow and Huai Valleys, YH and Northern Land, NL). Yield in the YH region was the greatest with both higher SN and KN, and SN had strong negative relationships with KN and KW. SN was the main factor correlated the variation of yield, especially in low yielding regions (UY and NL), suggesting breeding efforts should emphasize increasing SN in these environments. The role of KW and KN became increasingly important in high yielding region (YH), indicating that all yield components should be considered in breeding for high yielding environments.	en_US
dc.relation.ispartof	International Journal of Plant Production	en_US
dc.relation.isbasedon	10.1007/s42106-017-0007-6	en_US
dc.title	Spatial Patterns of Relationship Between Wheat Yield and Yield Components in China	en_US
dc.type	Journal Article
utslib.citation.volume	1	en_US
utslib.citation.volume	12	en_US
utslib.for	0607 Plant Biology	en_US
utslib.for	0703 Crop and Pasture Production	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Science
pubs.organisational-group	/University of Technology Sydney/Faculty of Science/School of Life Sciences
utslib.copyright.status	closed_access
pubs.issue	1	en_US
pubs.publication-status	Published	en_US
pubs.volume	12	en_US

Abstract:

© 2018, Springer International Publishing AG, part of Springer Nature. The considerable plasticity of wheat (Triticum aestivum L.) in reaching final yield is dynamically determined by three yield components: spike number m−2 (SN), kernel number spike−1 (KN) and 1000-kernel weight (KW). Understanding the contribution of yield components to the variation of grain yield under different production environments is essential for designing breeding programs and increasing grain production. This study analyzed 2 years of experimental data from the Chinese Variety Evaluation Program to explore the relationship between grain yield and yield components in four main winter wheat production regions. Correlation and path analysis were the main methods used in this paper. Yield and yield components were restricted by high temperature and lower sunshine hours at southern regions (Upper Yangtze Valleys, UY and Middle and Lower Yangtze Valleys, MLY). No relationship between yield and climate elements was found at northern region (Yellow and Huai Valleys, YH and Northern Land, NL). Yield in the YH region was the greatest with both higher SN and KN, and SN had strong negative relationships with KN and KW. SN was the main factor correlated the variation of yield, especially in low yielding regions (UY and NL), suggesting breeding efforts should emphasize increasing SN in these environments. The role of KW and KN became increasingly important in high yielding region (YH), indicating that all yield components should be considered in breeding for high yielding environments.

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http://hdl.handle.net/10453/131009