摘要
本研究利用四十个陆地棉亲本,经两年异地试验证明,以表型相关(r_p)矩阵代替遗传相关矩阵(r_g)作为距离分析的基础转换矩阵,不仅从统计角度分析是可行的;而且从应用角度分析,前者也具有相关结果一致性好,性状标准化合理,相关矩阵不会出现不正定性,年份之间可保证参与距离分析的性状完全一致,D^2估测结果一致性及聚类分析结果相符率高等优点.最长距离法的聚类范围大,并类合理且灵敏度高,聚类结果实用价值高,建议以表型相关矩阵(P)—主成份转换(C)—欧氏距离(E)—最长距离法(L).即PCEL法,作为棉花杂交亲本距离估测与聚类分析的适宜方法.
Two-year's experiment data using 40 parents of upland cotton (G. hir-sutum L. ) with 14 measured characters demonstrated that the phenotypic mean correlation (Rp) matrix can be used to replace the Rg matrix as the foundation of the distance estimation of the paraents. The former had a good stablity in two years, which character standardizing was rational and was always positive definite matrix. The character can be used in the analysis of phenotypic distance (Dp2) absolutely sameness.During two years, using the Rp had higher similarity of Dp2 and cluster results than the Rg. Compared to the different methods of cluster analysis, the longest distance method had a larger range of the cluster, higher sensitivity, rational result of the cluster and higher using value on the cotton breeding. The authers suggested that using phenotypic correlation matrix (P) -principal components transformation(C)-Euclidean distance(E)-the longest distance method of clustering(L), i. e. PCEL method be the best way for the distance estimation and cluster analysis of the cotton paraents.
出处
《华北农学报》
CSCD
北大核心
1991年第1期18-27,共10页
Acta Agriculturae Boreali-Sinica
关键词
棉花
杂交亲本
聚类分析
距离估测
Cotton
Correlation matrix
Distance estimation
Cluster analysis
