Genetic Inter-Relationship and Principal Component Analysis for Determination of the Selection Criteria in Mulberry Genotypes

Abstract

The identification of superior clones in mulberry breeding programs requires the knowledge on genetics of economic traits and efficient tools for selection. A field experiment was carried to evaluate two pseudo F2 populations of CSRS-1 × V1 and Kajli OPH × V1 for leaf yield and quality attributes during Kharif 2018. The objective of this study was to determine the interrelationship among different traits and to identify superior clones by principal component analysis. One way analysis of variance revealed that the progenies of both populations are highly significant for all quantitative traits studied indicating opportunity for genetic selection. Higher mean, standardized range and genotypic coefficient of variances was observed for fresh leaf weight, leaf area, primary shoots, total shoots length and leaf yield per plant. High to moderate heritability in broad sense and genetic advance in percent of mean was recorded for all the characters except for chlorophyll content index, specific leaf area, leaf moisture content and leaves per meter shoot. Phenotypic correlation coefficients and path analysis revealed that selection based on higher fresh leaf weight, primary shoots and total shoots length would be effective for increasing the leaf yield of mulberry. Platykurtic and positively skewed distribution noticed in these traits indicated the involvement of a several minor genes and dominance based complementary gene interaction suggests that rapid genetic gain under mild selection. PCA identified four principal components (PC) and explained 72 to 77% of total variation present in both the population. PC1, PC2, and PC3 were related to leaf productivity, quality and leaf size, respectively. PCA based index identified superior clones CV2, CV109, KV40, KV103 and KV169 may be further evaluated to develop improved mulberry varieties for subtropical sericulture.