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不同种群米槁果实与种子表型特征多样性分析
Analysis on Fruits and Seeds Phenotypic Diversity of Cinnamomum migao from Different Populations

DOI: 10.12677/HJAS.2023.134041, PP. 290-299

Keywords: 米槁,表型特征,变异分析,Pearson相关性分析,主成分分析,聚类分析
Cinnamomum migao
, Phenotypic Diversity, Variation Analysis, Pearson Correlation Analysis, Principal Component Analysis, Cluster Analysis

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Abstract:

为研究米槁果实和种子的表型差异,选取贵州和广西6个种群的米槁成熟果实和种子为材料,采用变异分析、Pearson相关性分析、逐步回归分析、主成分分析和聚类分析等方法研究其表型性状,同时,结合19个气候因子和3个地理因子分析各种群的9个表型特征。结果表明,群体内表型性状变异较小(变异系数4.61%~13.81%),群体间变异较大(变异系数12.05%~16.19%);9个表型特征中的果托直径、果形指数和种形指数与4个气候因子——最干旱季度平均降水量、降水季节性、最冷月平均气温、最干旱月份降水量和3个地理因子——经度、海拔、纬度有显著相关性;主成分分析结果表明:米槁果实与种子的形状因子、果实的表型特征、果托的表型特征前3个主成分的累积贡献率达81.750%;聚类分析结果表明:在欧氏距离为20时,米槁种群被分为两个大类,并以此为基础,把米槁分为大果型与小果型两种类型。通过本研究可以为作为中药材产业发展的米槁优良种质资源筛选提供方向。
To study the phenotypic differences of fruits and seeds of Cinnamomum migao, the mature fruits and seeds of C. migao from 6 populations in Guizhou and Guangxi were selected to analyze their phenotypic traits by using variation analysis, Pearson correlation analysis, stepwise regression analysis, principal component analysis and cluster analysis. Furthermore, 19 climatic factors and 3 geographical factors were combined to analyze 9 phenotypic characteristics of each population. The results showed that the variation of phenotypic characteristics was not significant within the population (coefficient of variation was 4.61%~13.81%), but much more obvious through different populations (coefficient of variation was 12.09%~16.19%). Among the 9 phenotypic characteristics, hypocarp diameter, fruit shape index and seeds shape index were significantly correlated with four climatic factors which are average precipitation in the driest season, precipitation seasonality, average temperature in the coldest month, precipitation in the driest month and three geographical factors which are longitude, altitude and latitude. The results of principal component analysis showed that the cumulative contribution rate of the first three principal components was 81.750%, including the shape factor of fruit and seed, the phenotypic characteristics of fruit and the phenotypic characteristics of hypocarp. The results of cluster analysis showed that the populations of C. migao could be divided into two groups when the Euclidean distance is 15, which means that C. migao could be grouped into two types, large and small fruit, consequently. This study will provide a direction for the screening of excellent C. migao germplasm resources in future.

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