Multivariate Analysis of Genetic Diversity among Maize Genotypes and Trait Interrelationships under Drought and Low N Stress

Multivariate analysis is the most popular approach for genetic variability estimation to study the
patterns of variation and their genetic relationships among germplasm collections to enhance their
use in crop breeding. The objectives of the present study were: (i) to assess the extent of genetic
diversity in a collection of Egyptian commercial maize hybrids and populations, through field
evaluation under water and N stressed and non-stressed conditions, using morphological data based
on Principle Component Analysis (PCA), (ii) to measure the genetic distance among these genotypes
using Agglomerative Hierarchical Clustering (AHC) analysis and (iii) to assess the relationship
between grain yield and yield-related traits of maize genotypes using genotype × trait (GT)-biplot
analysis. A two-year field experiment was conducted in a split-split plot design with 3 replications,
where 2 irrigation regimes, three N rates and 19 maize genotypes occupied the main plots, sub plots
and sub-sub plots, respectively. The germplasm was assessed for 21 agronomic traits. Highly
significant differences (P ≤ 0.01) were observed among the maize hybrids and populations for all
measured traits. Results of the GT biplot in the present study indicated that high values of 100-Kernel
weight, ears/plant, kernels/plant, kernels/row, plant height, nitrogen use efficiency, nitrogen utilization
efficiency, and grain nitrogen content and short ASI could be considered reliable secondary traits for
improving grain yield under stressed and non-stressed conditions. The highest genetic distance was
found between G9 (SC-2055) and each of G15 (American Early Dent), G18 (Midland) or G19 (Ried
Type). The AHC based on phenotypic data assigned the maize genotypes into five groups. The
different groups obtained can be useful for deriving the inbred lines with diverse features and
diversifying the heterotic pools.