Genetic analysis in ashwagandha [Withania somnifera (L.) Dunal]
Abstract
The present investigation was undertaken to decipher multivariate diversity, variability, genetic parameters and traits association in Ashwagandha (Withania somnifera (L.) Dunal), genotypes for the yield of a dry root, total alkaloids in root and agro-morphological traits. A total of 16 genotypes were evaluated at three experimental sites in Gujarat, India. A randomized complete block design with two replications was used to conduct the trial. Pooled ANOVA results showed highly significant differences (p < 0.001) among the genotypes (G), environments (E) and G x E interactions. Higher phenotypic and genotypic coefficient of variation values were recorded for yield and agro-morphological traits indicating variation and scope of improvement through selection based on phenotypes. Higher heritability associated with greater genetic advance for the majority of traits showed a prevalence of additive gene effect and thus, phenotypic selection will be more productive. Based on the similarity of traits within and between members of clusters, genotypes were divided into five clusters. The principal component analysis (PCA) showed that most of the differences (76.90%) were explained by the first four PCA. The correlation analysis implies that improving one or more components traits could result in enhancement in root yield and total alkaloid content in ashwagandha. Genetic variability was present for the traits under study in the tested genotypes. Hybridization of genotypes from different clusters could be able to yield new genotypes combining high yield and other desirable yield-contributing traits.
Key words: Multivariate diversity, variability, association analysis, cluster analysis, UPGMA, principal component, Withania somnifera
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