欢迎访问作物学报，今天是
作物学报

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 网络出版日期:2017-06-05
  • 通讯作者: 魏永胜, E-mail: wysh70@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 Published:2017-09-12 Published online:2017-06-05
  • Contact: Wei yonghseng, E-mail: wysh70@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.

RichHTML

PDF

1851

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

[1]Chamekha Z, Karmousb C, Ayadia S, Sahlia A, Hammamia Z, Frajc M B, Benaissaa N, Trifaa Y, Slim-Amaraaa H. Stability analysis of yield component traits in 25 durum wheat (Triticum durum Desf.) genotypes under contrasting irrigation water salinity. Agric Water Manag, 2015,152: 1–6
[2] Bhutto A H, Rajpar A A, Kalhoro S A, Ali A, Kalhoro F A, Ahmed M, Raza S, Kalhoro N A. Correlation and regression analysis for yield traits in wheat (Triticum aestivum L.) genotypes. Nat Sci, 2016,8: 96–104
[3] de Oliveira Gondim T C, Rocha V S,Sediyama C S, MirandaG V. Path analysis for yield components and agronomic traits of wheat under defoliation. Pesquisa Agropecuaria Brasileira, 2008, 43: 487–493
[4] Siney S M A,Saba J. Analysis of yield and yield components traits in twenty bread wheat genotypes under dry land conditions. Philippine J Crop Sci, 2015, 40: 78–84
[5] Okuyama L A, Federizzi L C, Neto J F B. Correlation and path analysis of yield and its components and plant traits in wheat. Ciencia Rural, 2004. 34: 1701–1708
[6] 田纪春, 邓志英, 胡瑞波, 王延训. 不同类型超级小麦产量构成因素及籽粒产量的通径分析. 作物学报, 2006, 32:1699–1705
Tian J C, Deng Z Y, Hu R B, Wang YX. Yield Components of super wheat cultivars with different types and the path coefficient analysis on grain yield. Acta Agron Sin, 2006, 32:1699–1705 (in Chinese with English abstract)
[7] Yagdi K. Path coefficient analysis of some yield components in durum wheat (Triticum durum Desf.). Pakistan J Bot, 2009, 41:745–751
[8] ?ifci E A. Estimate of heterosis, correlation and path analysis for grain yield per spike and some agronomic traits on durum wheat (Triticum durum Desf.). J Anim Plant Sci, 2012, 22:747–752
[9] Janmohammadi M, Movahedi Z, Sabaghnia N. Multivariate statistical analysis of some traits of bread wheat for breeding under rainfed conditions.J Agric Sci, Belgrade, 2014, 59:1–14
[10] Behmanesh S, Taghizadeh R, Zaefizadeh M. Analysis of yield and yield components in durum wheat. Int Res J Appl Basic Sci, 2013,4:3333–3337
[11]Carvalho I R, De Souza V Q, Nardino M, Follmann D N, Schmidt D, Baretta D. Canonical correlations between morphological traits and yield components in dual-purpose wheat. Pesquisa Agropecuaria Brasileira, 2015, 50: 690–697
[12] 金艳, 宋佳静, 朱统泉, 陈杰, 赵立尚.2001–2015年河南省审定小麦品种产量构成分析. 中国种业, 2016, (4):41–44
Jin Y, Song J J, Zhu T Q, Chen J, Zhao L S. Analysis for yield components of wheat varieties registered and released in Henan province in 2001–2015. China Seed Ind, 2016, (4):41–44 (in Chinese)
[13] Kline R B. Principles and Practice of Structural Equation Modeling. 3rd Edn. New York, NY: Guilford Press, 2011
[14]Grace J B. Structural Equation Modeling and Natural Systems. Cambridge,UK: Cambridge University Press, 2006
[15]Lamb E G, Shirtliffe S J, May W E, Structural equation modeling in the plant sciences: an example using yield components in oat. Can J Plant Sci, 2011, 91: 603–619
[16] Fornell C. A second Generation of Multivariate Analysis V1. New York, NY: Praeger Publishes, 1982
[17] Schermelleh-Engel K, Moosbrugger H, Müller H. Evaluating the fit of structural equation models: test of significance and descriptive goodness of fit measures. Methods Psychol Res Online, 2003, 8:23–74
[18] 王卫东. 结构方程模型原理与应用. 北京: 中国人民大学出版社, 2010
Wang WD. Theory and Application of Structural Equation Modeling , Beijing: China Renmin University Press, 2010 (in Chinese)
[1] 胡川, 赵凯男, 黄修利, 吴金芝, 任开明, 王贺正, 付国占, 黄明, 李友军. 一次灌溉下耕作方式和氮肥用量对旱地小麦产量和品质的影响[J]. 作物学报, 2026, 52(6): 1830-1846.
[2] 马胜乾, 王志平, 陈浩天, 窦淑贤, 张燕, 邓艾兴, 张卫建, 原向阳, 宋振伟. 秸秆还田下耕作方式与氮肥施用量对东北玉米产量及土壤团聚体的影响[J]. 作物学报, 2026, 52(6): 1802-1816.
[3] 张思思, 赵向辉, 周洋, 姚云凤, 朱荣昱, 董元杰, 胡国庆, 徐通, 刘兆新. 冬闲期翻耕和绿肥还田对连作花生田土壤理化性质和产量的影响[J]. 作物学报, 2026, 52(5): 1472-1486.
[4] 张宁宁, 滕雨菲, 任娜娜, 魏兴卓, 闫书豪, 樊可心, 王永宏, 陈文康, 张兴华, 朱万超, 徐淑兔, 薛吉全. 201份玉米自交系抗旱表型评价及可塑性分析[J]. 作物学报, 2026, 52(5): 1309-1325.
[5] 张颖星, 宋裕祯, 王跃, 曹越, 曹晓宁, 王瑞云. EMS诱导糜子优异性状突变体的筛选及表型分析[J]. 作物学报, 2026, 52(5): 1388-1400.
[6] 张鸿蓉, 王菲儿, 李盼, 仇海龙, 朱静, 赵连豪, 南运有, 何蔚, 樊志龙, 胡发龙, 柴强, 殷文. 减量20%灌水与25%有机肥替代化肥提高青贮玉米产量的光合特性[J]. 作物学报, 2026, 52(5): 1487-1500.
[7] 王宇诚, 张露, 刘阿康, 黄见良, 彭少兵, 袁珅. 基于产量差的作物大面积单产提升策略与展望[J]. 作物学报, 2026, 52(5): 1279-1290.
[8] 赵佳雪, 周龙昊, 郭岂源, 尚伦霄, 王涵, 刘志涛, 陈曦, 张晓佩, 宋宪亮, 毛丽丽. 长期秸秆还田与深松通过改善土壤环境与棉花光合特性提高滨海盐碱地棉花产量[J]. 作物学报, 2026, 52(5): 1548-1560.
[9] 郭星宇, 胡丹, 林苏期, 王梦凯, 谭文峰, 黄传琴. 生物炭配施化肥提高玉米‖大豆下玉米产量和土壤生态系统多功能性[J]. 作物学报, 2026, 52(5): 1536-1547.
[10] 张振, 冯连杰, 石玉, 于振文, 张永丽. 节水补灌下不同穗型小麦产量形成差异研究[J]. 作物学报, 2026, 52(5): 1522-1535.
[11] 闫安, 蒋昆炜, 王蓉圆, 田林, 张璐, 王韵, 徐建龙. 水稻剑叶小维管束数基因SVN7的鉴定与克隆[J]. 作物学报, 2026, 52(5): 1364-1372.
[12] 刘昕萌, 任昊, 张继波, 张吉旺, 赵斌, 任佰朝, 刘鹏, 王洪章. 茉莉酸甲酯(MeJA)缓解高温影响玉米雌穗分化的生理机制[J]. 作物学报, 2026, 52(5): 1561-1572.
[13] 王壮壮, 武紫君, 张永新, 张芯源, 袁丽雪, 陈如雪, 刘世举, 段剑钊, 冯伟, 王同朝, 王永华. 豫东南黏壤潮土区水氮优化协同提高冬小麦产量和氮素利用效率[J]. 作物学报, 2026, 52(5): 1501-1521.
[14] 蔡宏玮, 于爱忠, 姜科强, 王鹏飞, 王玉珑, 霍建喆, 庞小能, 尹波, 尚永盼. 干旱灌区有机肥替代部分化肥促进甜玉米产量提升的关键机制[J]. 作物学报, 2026, 52(4): 1166-1180.
[15] 崔雪梅, 柳妍娣, 刘景辉, 米俊珍, 武俊英, 赵宝平. 不同基因型燕麦强弱势粒生理特性与产量关系研究[J]. 作物学报, 2026, 52(4): 1220-1235.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
京ICP备15008789号-2