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不同李品种果实外观性状聚类分析 被引量:9

Cluster Analysis of Fruit Appearance Traits of Different Plum Cultivars
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摘要 以当地表现良好的15个李品种果实为试材,研究其单果重、核鲜重、可食率、果实纵径及横径、果形指数、果核纵径及横径、核形指数等9个外观性状品种间差异及相关性,并采用组间连接聚类法对15个供试材料进行了聚类分析。结果表明:品种间外观性状显示不同程度差异,单果重差异较大,核鲜重与可食率差异较小可忽略不计;果形指数≤1居多,说明15个李品种果形以圆形、扁圆形为主;而核形指数较大,说明核形以近椭圆形居多,且两者波动曲线接近同步。相关性分析显示:9个李品种外观性状间表现不同程度的正相关性,说明所选指标间的影响密切。其中单果重与可食率、果实纵径及横径、果核纵径及横径;果形指数与核形指数等存在极显著正相关。聚类分析在平方欧氏距离5的临界点可直接分为3类:小果型、大果型、中果型。分类特征主要表现在果实大小(单果重)上。 The differences and correlations among the 15 varieties with good local performance were studied,including single fruit weight,nuclear fresh weight,edible rate,fruit longitudinal diameter,transverse diameter,fruit shape index,fruit kernel longitudinal diameter,transverse diameter and nuclear shape index.The results showed that the appearance traits showed different degrees among different caltivars,the single fruit weight difference was large,and the difference between nuclear fresh weight and edible rate was negligible.The fruit shape is mainly round or oblate with the fruit shape index≤1,while the core shape is mostly near ellipse indicated the core shape index is larger,and the fluctuation curve of the two is close to synchronization.There was a significant positive correlation between fruit weight and edible rate,fruit longitudinal,transverse diameter,fruit core longitudinal,transverse diameter,fruit shape index,nuclear shape index and so on.The cluster analysis could be directly divided into three categories:small fruit type,large fruit type medium fruit type.The diagnostic characters?mainly manifested in fruit size(single fruit weight).
作者 宋永宏 杨复康 李静江 杨燕君 李华 杨晓华 SONG Yonghong;YANG Fukang;LI Jingjiang;YANG Yanjun;LI Hua;YANG Xiaohua(Pomology Institute Shanxi Academy of Agricultural Sciences,Shanxi Taigu 030815,China;Yangao Fruit Tree Station of Agricultural Rural Bureau,Shanxi Datong 038100,China)
出处 《果树资源学报》 2020年第3期6-9,共4页 Journal of Fruit Resources
基金 农科院生物育种工程项目(17yzgc045) 晋梅杏高接换优提质增效创优发展研究(YCX2018D2YX19) 杏新品种‘晋梅杏’示范推广(2019CGZH05-3)。
关键词 外观性状 聚类分析 Plum Appearance traits Cluster analysis
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