Abstract

Genetic diversity on 12 accessions of castor bean (Ricinus communis L.) collected from different origins of Iran was assessed under filed conditions. Accessions were evaluated in a randomized complete block design with three blocks. The data on 5 individuals in each block were recorded for 32 agro-morphological traits. The descriptive statistics for each one of 32 studied traits were calculated. Clustering of accessions into similarity groups was performed using Ward’s hierarchical algorithm based on squared Euclidean distances. Discriminant function analysis used to confirm the accuracy of grouping that produced by cluster analysis. In order to identify the patterns of morphological variation, principal component analysis (PCA) was conducted. Studied accessions showed high coefficient of variation for hollow seed number on primary raceme, secondary and tertiary branch fresh weight, secondary and tertiary branch dry weight, lamina leaf length and leaf length traits. The accessions based on studied traits were classified in 3 groups. Our results showed that, the most of studied accessions (75%) have been clustered together in group 2 indicating relatively low genetic variability in castor bean germplasm. Principal component analysis (PCA) revealed that the first six principal components accounted for 93% of the total variation. Among the studied traits, seed number on primary raceme as a yield component in castor bean showed positive correlation with the first component (PC1). Hollow seed number on primary raceme showed positive correlation with the second component (PC2). Oil percent presented negative correlation with PC2. According to breeding goal, breeders can chose accessions by considering appropriate PCs values. 

Key words: Agro-morphological traits, descriptive statistics, cluster analysis, discriminant function analysis, genetic diversity, principal component analysis.