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文冠果种实性状变异规律及优良单株选择 被引量:10

Variation Pattern of Fruit and Seed Characters and Superior Individual Selection of Xanthoceras sorbifolium
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摘要 为明确文冠果种实性状变异规律,以5个种源的文冠果植株为研究对象,连续3年进行种实采集并测定相关性状。运用方差分析、相关性分析对13个种实性状进行分析,同时运用主成分分析、模糊隶属函数法以及多维空间坐标向量综合评定值累加法进行优良单株选择。结果显示:参试单株产量性状变异较大,单位投影面积种子产量变异系数最大,种子含油率变异系数较小。13个种实性状构成5个主因子。用主成分分析法选择高产型、高油型、高产高油型优良单株,得到的现实增益均较高;说明选出的不同类型优良单株具有显著的优异性,可在生产中推广;利用3种方法选择复合型优良单株,总体结果较接近。 For the variation pattern of fruit and seed characters in Xanthoceras sorbifolium , the fruits and seeds of each individual were collected to measure the related characters for three consecutive years in five provenances. Variance analysis and correlation analysis were used to analyze 13 fruit and seed characters. Principal component analysis, subordinate-function-value method and multidimensional coordinate-synthetic-evaluation method were used to select superior individuals. There were great variations in yield characters among individuals. The highest variation coefficient was observed in seed yield per unit projective area, while low variation coefficient occurred in seed oil concentration. In addition, thirteen fruit and seed characters constituted five main factors. F1 was yield factor, and F2 was oil concentration factor. Superior individuals of high-yield type, high-oil concentration type, and high-yield and-oil concentration type were selected by principal component analysis. The real gains of each type were very high, which showed that they had remarkable superiority and could be popularized in production, and the results of compound superior individual selection by the three methods were similar.
作者 张毅 敖妍 刘觉非 赵磊磊 张永明 Zhang Yi;Ao Yan;Liu Juefei;Zhao Leilei;Zhang Yongming(Beijing Forestry University,Beijing 100083,P. R. China;Forestry Seedling Station of Chifeng City;Wengniuteqi Forestry Bureau of Chifeng)
出处 《东北林业大学学报》 CAS CSCD 北大核心 2019年第9期1-5,共5页 Journal of Northeast Forestry University
基金 国家自然科学基金青年基金项目(31600241) 中央高校基本科研业务费专项资金(2015ZCQ-LX-02)
关键词 文冠果 种实性状 变异规律 优良单株 主成分分析 Xanthoceras sorbifolium Bunge Fruit and seed characters Variation pattern Superior individual Principal component analysis
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