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东北茶藨子果实性状变异研究

Fruit Characters Variation of Ribes mandshuricum
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摘要 选取东北茶藨子4个天然群体共60个单株为试验样本,利用变异分析、巢式方差分析、多重比较、相关分析及主成分分析等方法,探讨东北茶藨子生长及果实性状的相关规律及其在天然群体间和个体间的变异特征。结果表明:果实各性状平均变异系数为21.95%,变异幅度为5.15%~30.64%;东北茶藨子5个营养性状在群体内达到差异极显著,3个性状在群体间达到差异极显著水平,平均表型分化系数22.56%,其中群体间变异(21.81%)小于群体内变异(74.87%);果实各营养性状间大部分存在极显著正相关关系。东北茶藨子的13个性状主成分分析可归为2大类,在培育不同经济目标的优良单株时,可以通过计算主成分得分值进行快速准确的选择。总体上来说,东北茶藨子天然群体果实性状表型分化处于中等水平,变异主要来自群体内部变异。 The correlation between growth and fruit characters of Ribes mandshuricum and its variation charac- teristics among natural populations and individuals was studied based on variation analysis, nested analysis of vari- ance, multiple-comparison, correlation analysis and principal component analysis, 60 individuals which selected from 4 different natural populations were took as test sample. Results show that the average variation coefficient of each character was 21.95%, the variation range was 5.15%-30. 64%. There were significantly differences between 5 nutrition characters within R. mandshuricum populations, and 3 nutrition characters showed extremely significantly differences within R. mandshuricum populations. The mean phenotypic differentiation coefficient of all characters was 22.56%, and the variation between populations (21.81%) was lower than that within populations (74. 87%). There was significantly extremely positive correlated between most fruit characters. According to principal compo- nents analysis, 13 characters of R. mandshuricum could be divided into two groups so that calculate the main com- ponent score for fast and accurate selection while cultivating superior individuals of different economic objectives. In a word, The fruit characters phenotypic differentiation of R. mandshuricum natural populations was moderate level. The main variation was within populations.
出处 《西南林业大学学报(自然科学)》 CAS 北大核心 2017年第6期23-29,共7页 Journal of Southwest Forestry University:Natural Sciences
基金 中国林科院林业新技术所基本科研业务费专项(CAFINT2015C15)资助
关键词 东北茶蔗子 果实 遗传变异 相关分析 主成分分析 Ribes mandshuricum, fruit, genetic variation, correlation analysis, principal component analysis
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