Evaluation of Genetic Variability and Diversity Analysis through Hierarchical Clustering in Rice (Oryza sativa L.) Accessions
Aparna *
Govind Ballabh Pant University of Agriculture and Technology, Pantnagar, India and Faculty of Agriculture, Jagan Nath University, Chaksu, Jaipur, India.
Indra Deo
Govind Ballabh Pant University of Agriculture and Technology, Pantnagar, India.
Prerna Dogra
Department of Soil Science and Agricultural Chemistry, SKNAU, Jobner, India.
Sanjiv Kumar
Faculty of Agriculture, Jagan Nath University, Chaksu, Jaipur, India.
Smrutishree Sahoo
K. R. Mangalam University, Gurugram, Haryana, India.
*Author to whom correspondence should be addressed.
Abstract
Rice (Oryza sativa L.) is a major staple crop, and genetic improvement of yield and associated traits depends on the availability and effective utilisation of genetic variability within breeding materials. Assessment of agro-morphological variation, heritability, genetic advance, and genetic diversity can facilitate the identification of promising genotypes and genetically divergent parents for rice improvement. Therefore, evaluating variability and diversity among rice accessions is important for guiding effective selection and future breeding programmes. This study evaluated genetic variability and agro-morphological diversity among 136 rice accessions comprising 132 IIRON lines and four local checks using 14 yield and yield-related traits. Variability was assessed through the genotypic coefficient of variation (GCV), phenotypic coefficient of variation (PCV), broad-sense heritability, genetic advance as a percentage of the mean, and hierarchical cluster analysis. PCV exceeded GCV for all traits, although the differences were narrow for several characters, suggesting comparatively limited environmental influence. Flag leaf area recorded the highest GCV (23.84%) and PCV (23.91%), while days to maturity showed the lowest values (4.44% and 4.63%, respectively). Broad-sense heritability was high for all traits, ranging from 68.81% for grain yield per plant to 99.78% for flag leaf length. High heritability together with high genetic advance was observed for effective tillers, flag leaf traits, grain length-to-breadth ratio, test weight, and grain yield per plant. Hierarchical clustering based on standardised adjusted means, Ward’s linkage method, and squared Euclidean distance separated the 136 accessions into four clusters containing 47, 9, 54, and 26 accessions, respectively. Cluster IV recorded the highest mean grain yield per plant (20.57 g) and superior mean values for several associated traits. The results indicate substantial exploitable variability among the evaluated accessions and identify contrasting groups that may be useful for selection and parental choice in subsequent breeding work.
Keywords: IIRON accessions, genetic variability, heritability, genetic advance, agro-morphological traits, hierarchical cluster analysis