Study of genetic variability and diversity analysis in maize (Zea mays L.) by agglomerative hierarchical clustering and principal component analysis

The most comprehensive study was undertaken to investigate genetic variability, character association studies and diversity analysis for yield and yield attributing traits in sixty-five maize genotypes along with five checks raised in Augmented block design II and observations were recorded on fourteen morphological traits. For all the traits, the analysis of variance revealed significant variance. PCV and GCV was high for anthesis silking interval. High genetic advance as per cent of mean along with heritability was recorded for anthesis silking interval, number of tassel branches, cob length, plant height and tassel height. This showed the effectiveness of selection for these traits. Character association analysis confirmed that grain yield per plant had a positive significant association with number of kernel rows per cob, number of kernels per row, cob breadth, cob length, 100 seed weight, shelling percentage and plant height. This implies that by selecting for these traits, grain yield per plant can be improved significantly. Path analysis for the attributed traits showed the direct effect of shelling percentage and plant height on single plant yield. Consequently, an emphasis on these traits could lead to the successful identification of higher yielding genotypes. Based on agglomerative hierarchical clustering, genotypes UMI1113, UMI1153, UMI 653-2-3, UMI1131-5 and UMI1076-5-4-2 can be used as parental lines in the hybridization programme. PCA biplot showed that number of kernel rows per cob, number of kernels per row, cob placement height, plant height and single plant yield mostly contributed towards variability. Furthermore, these parental lines should be assessed for their general combining ability and specific combining ability to generate stable and superior hybrids for better yield performance.