Assessment of Genetic Diversity in Sorghum (Sorghum bicolor (L.). Moench) Genotypes using Principal Components and Cluster Analysis

Aims: Understanding and using the genetic variation in sorghum genotypes is crucial for enhancing the crop because sorghum is a significant grain yield crop in worldwide. Selective breeding will be made possible by a thorough understanding of the genetic diversity among the genotypes. So, it will soon be possible to profile the genetic diversity of sorghum. In the current study, the genetic diversity of 28 sorghum genotypes was examined using 10 quantitative characters.

Study Design: Randomized block design (RBD) with four replications.

Place and Duration of Study: Tamil Nadu Agricultural University, Coimbatore, Tamil Nadu, India. Between February 2022 and May 2022.

Methodology: The descriptive statistical analysis, analysis of variance (ANOVA) and correlation analysis were carried out for each of the 10 quantitative characters. Using principal component analysis (PCA), the proportion of each trait's contribution to overall genetic variation was looked at. Plotting the first two Principal components in opposition to one another allowed the identification of patterns of variability among genotypes and characteristics. Using the Ward’s linkage approach, hierarchical clustering was carried out on the Euclidean distance matrix.

Results: Descriptive statistics and analysis of variance (ANOVA) shows the significant genetic variability inherent in the sorghum genotype at 1% level of significance. Correlation revealed the connection between panicle width and 1000 seed weight to grain yield per plant was quite favorable and significant. The Scree plot of the variables gives that the first three Principal components (PC), which have eigenvalues greater than one, collectively explained about 74.15% of the total variation. By Biplot, ICSB 541, ICSV 15013, ICSB 52, ICSB 24001 and Macia show higher value of Panicle width, 1000 Seed weight and Grain yield per plant. B35 has considerably longer and wider leaves. By Cluster analysis, cluster II is important which had the greatest mean values for panicle width, 1000 seed weight and Grain yield per plant. Cluster II and III had the maximum intercluster distance (4.43).

Conclusion: Based on the quantitative character data, the genotypes ICSB 541 and ICSV 15013 were shown to be superior for earliness and high yield for grain yield in this study. Therefore, in order to produce better types, these genotypes should be utilized in subsequent breeding programmes.