应用聚类分析对甘蓝型油菜品种进行分组,以进行差异检验

O. Y. Dydiv, V. Khareba, O. Khareba, N. Leshchuk, N. Orlenko, O. B. Orlenko
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引用次数: 0

摘要

目的。利用形态特征的聚类分析简化甘蓝型油菜变种 italica 的鉴定,并将相似品种分组进行差异检验。 方法。工作中使用了分析、数学和统计方法。作为对所获结果进行统计处理的输入信息,使用了乌克兰植物品种检验研究所自动信息系统数据库中关于独特性、均匀性和稳定性(DUS)检验结果的信息。使用 IBM SPSS 统计软件包 "社会科学统计软件包 "进行了聚类建模。 研究结果根据 32 个特征对西兰花品种进行了形态描述,以检查其独特性、一致性和稳定性。后者的形态代码公式由植物无性器官和生殖器官识别特征表现的相应代码组成,是初始数据的来源。在以 32 个形态特征描述的 41 个品种中,发现只有两组品种的识别特征相似。有两类变量被用作模型参数:目标--特征 "头部:花青素颜色",焦点--"头部:颜色"。全部特征列表如下:"植株:高度(收获成熟时)"、"叶片:位置(头部形成初期)"、"叶片:波浪边缘"、"叶片:起泡"、"叶柄:长度"、"头部:颜色"、"头部:花青素颜色"、"头部:密度"、"花朵:颜色"、"花朵:黄色强度"、"雄性不育"。利用计算机建模,形成了由 17 个相似西兰花品种和 9 个对照对象(品种)组成的群组,其识别涉及 11 个形态特征。 最后得出结论。为了在测试甘蓝品种差异的过程中寻找区别特征,根据叶片在头部形成初期的位置、叶片边缘的波浪状、叶片板的水泡、叶柄长度、头部颜色、花青素的存在和黄色的强度等形态特征对西兰花进行了分组。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application of cluster analysis for grouping Brassica oleracea var. italica varieties for the difference test
Purpose. To use cluster analysis of morphological cha­racters to simplify the identification of Brassica oleracea var. italica and form groups of similar varieties for the test of difference. Methods. Analytical, mathematical and statistical methods were used in the work. As input information for the statistical processing of the obtained results, information on the results of the examination for distinctness, uniformity and stability (DUS) from the database of the Automated Information System of the Ukrainian Institute for Plant Varieties Examination was used. Cluster modelling was carried out using the IBM SPSS Statistics “Statistical Package for the Social Sciences”. Results. A morphological description of broccoli varieties was carried out on the basis of 32 characteristics for the examination of distinctness, uniformity and stability. The morphological code formulae of the latter, composed of the corresponding codes for the manifestation of identifying characteristics of vegetative and generative organs of plants, served as a source of initial data. Out of 41 varieties described by 32 morphological characteristics, only two groups were found to be similar in terms of the identifying characteristics of the varieties. Two types of variables were used as parameters of the model: target – characteristic “Head: anthocyanin colour”, focal – “Head: colour”. The full list of characteristics was as follows “plant: by height (at harvest maturity)”, “leaf: position (at beginning of head formation)”, “leaf blade: wavy edge”, “leaf blade: blistering”, “petiole: by length”, “head: colour”, “head: anthocyanin colour”, “head: by density”, “flower: colour”, “flower: intensity of yellow colour”, “male sterility”. Using computer modelling, clusters of 17 similar broccoli varieties and 9 control objects (varieties) were formed, the identification of which involved eleven morphological characteristics. Conclusions. In order to search for distinguishing characteristics in the process of testing the difference of cabbage varieties, broccoli was grouped into clusters according to such morphological characteristics as the position of the leaf at the beginning of the formation of the head; waviness of the edge of the leaf blade; blistering of the leaf plate; petiole length; head colour; presence of anthocyanin and intensity of yellow colour.
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