Multivariate Analysis in Maize (Zea mays L.) Inbred Lines
Abstract
Maize (Zea mays L.) is a leading cereal crop whose genetic improvement depends largely on the availability of diverse and divergent parents. The present investigation was undertaken to assess the mean performance and to quantify the genetic divergence among thirty maize inbred lines for sixteen quantitative characters. The experiment was conducted during the Kharif season of 2023–24 at the Research Farm of the Faculty of Agriculture Science and Technology, AKS University, Satna (M.P.), India, using a randomised complete block design with three replications. Analysis of variance revealed highly significant differences among the genotypes for all sixteen characters, and wide ranges were recorded, particularly for grain yield per plant (108.69–223.99 g), flag leaf length and shelling percentage, indicating the presence of substantial genetic variability. Genetic divergence was estimated using Mahalanobis’ D² statistic, and the genotypes were grouped into four clusters by the non-hierarchical Euclidean clustering method. Clusters I and IV were the largest, each comprising ten genotypes, whereas Clusters II and III contained five genotypes each. The maximum inter-cluster distance was observed between Clusters II and III (55.18) and the minimum between Clusters I and IV (22.00). Cluster I recorded the highest mean grain yield per plant, Cluster II the tallest plants and highest test weight, and Cluster IV the highest shelling percentage with the earliest flowering, although the clusters differed only modestly in mean performance for most yield components. The genotypes HKL-163, AMI-106 and AMI-118 emerged as the most promising parents. Hybridisation between genotypes drawn from the divergent Clusters II and III is suggested for exploiting heterosis and recovering desirable transgressive segregants in maize.