Application of cluster analysis and principal component analysis in the development of new vine varieties
2007
Rojchev, V. | Dimova, D. | Bozhinov, B.
The possibilities for the application of cluster analysis and principal component analysis (PCA) in the development of new vine varieties have been studied. It has been established that in the seeded and seedless seedlings of F1 progeny of the Super Early Bolgar X Kishmish Hyshrau cross the most variable traits are: coefficient of shoot productivity, yield, total number of shoots and fruiting shoots, berry width and total number of clusters. Six of the principal components represent 88.05% of the total variability of traits. The seedless seedlings of the same cross are characterized by a comparatively high degree of phenotypic homogeneity and they form two groups, only 94.37% of the total variability is explained with the help of five principal components. In order to be efficient, the selection in these plant groups should be carried out in accordance with the traits which correlate to the first and second principal component in the highest degree.
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Эту запись предоставил Institute of Agricultural Economics