International Journal of Plant Production

, Volume 12, Issue 1, pp 61–71 | Cite as

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

Original Paper
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Abstract

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.

Keywords

Wheat yield Yield components Spike number Kernel number Kernel weight Climate elements 

Notes

Acknowledgements

This work is supported by the National Natural Science Foundation of China (Grant Nos. 41371119 and 31400416) and by the Natural Science Foundation of Jiangsu Province (Grant No. BK20140988).

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Jiangsu Key Laboratory of Agricultural Meteorology, College of Applied MeteorologyNanjing University of Information Science and TechnologyNanjingChina
  2. 2.USDA-ARS, Water Management and Systems Research UnitFort CollinsUSA
  3. 3.State Key Laboratory of Soil Erosion and Dryland Farming on the Loess PlateauNorthwest A&F UniversityYanglingChina
  4. 4.School of Life SciencesUniversity of TechnologySydneyAustralia
  5. 5.College of Resources and EnvironmentUniversity of Chinese Academy of ScienceBeijingChina

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