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Application of Multivariate Analysis to Access Selected Rice Germplasm Phenotypic Diversity

机译:多元分析在选择水稻种质表型多样性中的应用

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摘要

Without variability, it is not possible to conduct a plant breeding program. Germplasm is hence the critical first step in initiating a breeding program. Diversity in O. glaberrima accessions is enormous. It needs to be organized and characterized in order to facilitate its use by plant breeders. Two principal components (PRIN1) and (PRIN2) accounted for most of the variability observed in characters studied. PRIN 1 accounted for 56% of the phenotypic and morphological variation. The PRIN 1 was loaded on plant height, number of panicle, biomass wet weight, panicle wet weight and grain yield traits. PRIN 2 accounted for 23% of the variation. PRIN 2 was loaded on biomass wet weight, biomass dry weight, panicle wet weight, panicle dry weight, and harvest index traits. The test for univariate statistics described individual variable to explore pattern of response to variation showed strong statistical significantly (P<0.001) on phenotypic differences in all the variables that were measured. These traits studied are the most important contributing to the overall variability. The dendogram produced grouping that defined nine distinct clusters and minimum genetic distance between clusters varies from 0 to 5. All the selected Oryza glaberrima accessions and the Oryza sativa were distributed across the nine clusters respectively.
机译:没有可变性,就不可能进行植物育种程序。因此,种质是启动育种计划的关键的第一步。 O. glaberrima品种的多样性是巨大的。为了便于植物育种者使用,需要对其进行组织和表征。两个主要成分(PRIN1)和(PRIN2)构成了所研究字符中观察到的大部分变异性。 PRIN 1占表型和形态变异的56%。将PRIN 1加载到植物高度,穗数,生物量湿重,穗湿重和谷物产量性状上。 PRIN 2占变异的23%。将PRIN 2加载到生物质湿重,生物质干重,穗湿重,穗干重和收获指数性状上。单变量统计量的测试描述了单个变量以探索对变异的响应模式,显示在所有测量变量中,表型差异具有很强的统计学显着性(P <0.001)。研究的这些特征是对整体变异性最重要的贡献。树状图产生的分组定义了9个不同的簇,簇之间的最小遗传距离从0到5不等。所有选定的Oryza glaberrima品种和Oryza sativa分别分布在这9个簇中。

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