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Relationships between Primary and Secondary Yield Components of a Maize Population after 13 Stratified Mass Selection Cycles

机译:13个分层质量选择循环后玉米种群初级和次级产量构成之间的关系

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摘要

This research aimed to identify the relationships between the primary and secondary components of the maize yield using the techniques of canonical correlation and factors analysis. The base population was composed of nine randomized crossing hybridsin an isolated field, in the years 2006-2012. Canonical correlations were estimated between the variable group consisting of primary (Gl) and secondary (Gil) yield components. To Factor Analysis (FA), we chose a number of common factors equal to the number of eigen values higher than the existing unit in the phenotypic correlations matrix of variables and the orthogonal factor model was opted. Primary and secondary yield components of maize grains are not independent. Inter-group associations are established by plants with higher height, stem diameter, dry weight and lower ear height, which positively influence primary yield components (dry ear weight, ear length and hundred-grain weight). Factor analysis allowed to reduce a large number of original variables observed to a small number of abstract variables and can be used to complement the canonical variables technique.
机译:这项研究旨在使用典型相关技术和因子分析技术来确定玉米产量的主要成分和次要成分之间的关​​系。在2006-2012年间,基本种群由9个随机杂交杂种组成。估计了由主要(G1)和次要(Gil)产量构成的变量组之间的典范相关性。在因子分析(FA)中,我们选择了一些等于变量表型相关矩阵中比本征值高的特征值的公共因子,并选择了正交因子模型。玉米籽粒的初级和次级产量成分不是独立的。组间关联是由具有较高身高,茎直径,干重和较低穗高的植物建立的,这些植物对主要产量成分(穗干重,穗长和百粒重)产生积极影响。因子分析可以将观察到的大量原始变量减少为少量的抽象变量,并且可以用于补充规范变量技术。

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