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油菜育种亲本主要性状相关性及主成分分析 被引量:15

Correlation and Principal Components Analysis of the Main Agricultural Traits of Rapeseed Breeding Parents
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摘要 为了有效评价油菜不同亲本材料,筛选获得可用于油菜育种的优良亲本,并对油菜性状基本遗传规律进行探讨。以国内外18个油菜育种亲本为材料,对油菜11个主要农艺性状进行了相关性和主成分分析。油菜亲本间主要农艺性状的表型差异较大,不同性状的变异系数介于0.09~0.31之间,其中单株产量的变化最大,株高的变化最小;油菜主要农艺性状的相关性差异明显,角果数相关性状与单株产量的相关性表现较好,而不同部位分枝间距与其他性状的相关性均较差;在获得的4个主成分中,除第1主成分主要由角果数和单株产量构成外,其余3个主成分均以不同部位分枝间距为主。油菜育种实践中应同时注重对主要目标性状及其相关性状的有效改良,本研究将为油菜种质有效利用和油菜性状改良提供一定的科学依据。 In order to assess the different rapeseed lines effectively and select the elite lines for rapeseedbreeding, as well as discuss the basic heredity laws of rapeseed traits, the correlation analysis and the principalcomponents analysis were carried out on eleven agricultural traits of eighteen rapeseed breeding lines. Therewere great differences among the main agricultural traits of rapeseed breeding parents. The variation coefficientof the different traits ranged from 0.09 to 0.31, the highest was found for yield per plant and the least was foundfor plant height. The correlations of the main agricultural traits were different. The significant correlation wasfound between the related silique number and yield per plant, and the bad correlation was found between thedistance of branches and other traits. The four main principal components were obtained in the principalcomponents analysis of the main agricultural traits. Except that the first principal component consisted ofsilique number and yield plant, the other three principal components were mainly constituted by distance ofbranches. Both the main objective traits and its related traits should be emphasized in the effectiveimprovement of rapeseed breeding. All these results would provide some basis for the effective utilization ofrapeseed germplasm and the improvement of rapeseed traits.
出处 《中国农学通报》 2015年第27期147-152,共6页 Chinese Agricultural Science Bulletin
基金 河南科技厅科技攻关项目"苜蓿栽培品种DNA指纹图谱构建及遗传多样性研究"(KJT142102110171)
关键词 油菜 主要性状 相关性分析 主成分分析 rapeseed the main agricultural traits correlation analysis principal components analysis
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