玉米,图像处理,穗粒重,果穗几何特征,数量关系," /> 玉米,图像处理,穗粒重,果穗几何特征,数量关系,"/> maize (Zea mays L.),image analysis,grain yield,ear geometry,quantitative relations
,"/> <font face="Verdana">玉米穗粒重与果穗三维几何特征关系的定量研究</font>

中国农业科学 ›› 2010, Vol. 43 ›› Issue (21): 4367-4374 .doi: 10.3864/j.issn.0578-1752.2010.21.005

• 耕作栽培·生理生化·农业信息技术 • 上一篇    下一篇

玉米穗粒重与果穗三维几何特征关系的定量研究

杨锦忠,张洪生,赵延明,宋希云,王新勤   

  1. (青岛农业大学数字农业研究中心)
  • 收稿日期:2010-04-20 修回日期:2010-05-16 出版日期:2010-11-01 发布日期:2010-11-01
  • 通讯作者:

Quantitative Study on the Relationships Between Grain Yield and Ear 3-D Geometry in Maize#br#

YANG Jin-zhong, ZHANG Hong-sheng, ZHAO Yan-ming, SONG Xi-yun, WANG Xin-qin#br#   

  1. (青岛农业大学数字农业研究中心)
  • Received:2010-04-20 Revised:2010-05-16 Online:2010-11-01 Published:2010-11-01

摘要:

【目的】从穗粒重与果穗三维几何关系的角度探索籽粒产量的制约因素,寻找进一步提高玉米产量的途径。【方法】利用图像处理技术采集了10个品种的果穗几何特征,分析了穗粒重对果穗几何特征组合的回归,以及穗粒重与穗大小特征的相关性。矩形度定义为果穗面积占其外接矩形面积的比例,分别与穗长+穗粗、穗面积、穗体积组合建立回归方程。【结果】上述3种组合方程,分别解释了品种间籽粒产量总变异的77.7%、70%和78.7%,矩形度的贡献大于或者约等于穗大小几何特征。同样结构的回归方程在矫正品种产量后,解释了环境间籽粒产量总变异的81.3%—82.0%,矩形度的贡献小于穗大小几何特征。穗大小对籽粒产量的简单决定系数为:在品种间,三种维数的大小特征都不显著;在环境间,穗长、穗粗、穗面积、穗体积分别为0.387、0.167、0.590、0.571。【结论】穗大小单一特征的重要性次序为:穗体积>穗面积>穗长、穗粗,穗矩形度是反映穗形态的一个重要性状,与穗大小特征相组合,能够高精度预测穗粒重。

关键词: 玉米')">玉米, 图像处理, 穗粒重, 果穗几何特征, 数量关系

Abstract:

【Objective】 Ear geometry conditions the grain yield potential in maize. The objective of this study is to quantify the relationships between grain yield and ear 3-D geometry in maize as a pathway to higher crop yield. 【Method】 Ear geometric features were extracted using image analysis from images of ears for each of 10 cultivars in maize. Both grain yield correlations to ear sizes at different geometric dimensions and its regressions as functions of ear shape and size combinations were studied. Three regression equations were built with 3 combinations as predictors of ear extent (EE) and ear length (EL) and width (ED), EE and ear area (EA), and EE and ear volume (EV). 【Result】 These equations in that order explained 77.7%, 70% and 78.7% of total grain yield variations among 10 cultivars studied, 81.7%, 81.3% and 82.% of that among micro-envionments within fields. Simple determination coefficients between grain yield and ear sizes were not significant for EL, EW, EA or EV when evaluated cross all cultivar averages, while that were 0.387, 0.167, 0.590, 0.571 for EL, EW, EA and EV, respectively, in the background of micro-envionments within fields. 【Conclusion】 EE is a novel important trait featuring ear geomotry in maize, and its combinations with ear geometric size features may predict grain yields at high accuracy. Size features ranks of importance as an indirect indicator of grain yields are EV>EA>EL and EW.

Key words: maize (Zea mays L.)')">maize (Zea mays L.), image analysis, grain yield, ear geometry, quantitative relations