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作物学报 ›› 2017, Vol. 43 ›› Issue (09): 1395-1400.doi: 10.3724/SP.J.1006.2017.01395

• 耕作栽培·生理生化 • 上一篇    下一篇

结构方程模型在冬小麦农艺性状与产量关系分析中的应用

郑立飞2,尚一斐2,李学军3,冯浩4,魏永胜1,*   

  1. 1西北农林科技大学生命科学学院, 陕西杨凌 712100; 2西北农林科技大学理学院, 陕西杨凌 712100; 3西北农林科技大学农学院, 陕西杨凌 712100; 4西北农林科技大学国家节水灌溉杨凌技术研究中心, 陕西杨凌 712100
  • 收稿日期:2016-12-07 修回日期:2017-05-10 出版日期:2017-09-12 发布日期:2017-06-05
  • 通讯作者: 魏永胜, E-mail: wysh70@nwsuaf.edu.cn E-mail:zhenglifei@nwsuaf.edu.cn
  • 基金资助:

    本研究由国家高技术研究发展计划(863计划)项目(2013AA102904), 西北农林科技大学基本科研业务费专项资金(2014YB023)和西北农林科技大学本科优质课程建设项目资助。

Structural Equation Model for Analyzing Relationshipbetween Yield and Agronomic Traits in Winter Wheat

ZHENG Li-Fei 2,SHANG Yi-Fei 2,LI Xue-Jun3,FENG Hao4,WEI Yong-Sheng1,*   

  1. 1 College of Life Sciences, Northwest A&F University, Yangling 712100, China;2 College of Science, Northwest A&F University, Yangling 712100, China; 3 College of Agronomy, Northwest A&F University, Yangling 712100, China; 4 China Water Saving Irrigation Institute, Northwest A&F University, Yangling 712100, China
  • Received:2016-12-07 Revised:2017-05-10 Online:2017-09-12 Published:2017-06-05
  • Contact: Wei yonghseng, E-mail: wysh70@nwsuaf.edu.cn E-mail:zhenglifei@nwsuaf.edu.cn
  • Supported by:

    This study was supported by the National High Technology Research and Development Program of China (2013AA102904), the Special Funds for Research Activities in Northwest A&F University (2014YB023), and the Quality Curriculum project in Northwest A&F University.

摘要:

为探讨冬小麦主要农艺性状对产量的影响及各性状间的相互作用, 采用结构方程模型对2010—2011年度国家冬小麦品种试验中长江上游组(19个品种19个试点)的数据进行了分析, 调查性状包括产量(GY)、穗粒数(GNP)、基本苗(BS)、单位面积穗数(SN)、生育期(GD)、千粒重(TGW)和株高(PH)。其变异系数为GY>GNP>SN>BS>PH>TGW>GD; 与产量的相关程度(相关系数绝对值)为GNP>BS>SN>GD>TGW>PH; 在多元回归分析中对产量的效应为SN>GNP>TGW>BS>GD>PH; 在结构方程模型中对产量的综合效应(直接效应与间接效应之和)为BS>GNP>TGW>SN>PH>GD。结构方程模型既体现了主要农艺性状对产量的直接效应, 也体现了对产量的间接效应, 并且作为先验模型, 可结合作物生理特性解释主要农艺性状对产量的影响。本研究结果表明, 应重视大穗多穗兼顾型冬小麦品种的选育。

关键词: 冬小麦, 产量, 农艺性状, 结构方程模型

Abstract:

This study aimed at understanding the relationshipbetween winterwheat yield andmajor agronomic traits using structural equation model. The parameters collected from the 2010–2011 National Winter Wheat Region Trail for Upper Yangtze River Group (19 varieties in 19 locations) were grain yield (GY), grain number per spike (GNP), density of basic seedlings (BS), spike number per ha (SN), growth duration (GD), thousand-grain weight (TGW), and plant height (PH). The variance coefficient in structural equation model showed a trend ofGY > GNP > SN > BS > PH > TGW > GD. According toPearson correlation, the correlation levels with yield was GNP > BS > SN > GD > TGW > PH. The effect of a single trait on yield was SN > GNP > TGW > BS > GD > PH according to multiple regression analysis and BS > GNP > TGW > SN > PH > GD according to the sum of direct and indirect effects in structural equation model. Both direct and indirect effects of agronomic traits in winter wheat on yield can be explained by structural equation model. As a prior experimental model, structural equation model can be used to analysis the complex relationship between crop physiological properties and wheat yield.. Our results suggest that large- and multi-spikes need to be considered simultaneously in winter wheat breeding.

Key words: Winter wheat, Yield, Agronomic traits, Structural equation model

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