Multivariate analysis of agronomic characteristics in some Egyptian barley landraces: a field-based quantitative study

Abstract Background Barley is a significant cereal crop in Egypt, with the potential to be used for its endurance against harsh environmental conditions, particularly in arid and semi-arid regions. The current study was conducted to assess the genetic diversity and relationships among agronomic traits of 81 Egyptian barley landraces using multivariate statistical tools like principal component analysis, cluster analysis, path analysis, and correlation analysis. The parameters recorded were days to heading, days to maturity, plant height, grain yield, spikes per square meter, grains per spike, and thousand-grain weight. Results The Pearson correlation heatmap showed strong relationships between the agronomic characteristics assessed in 81 barley landraces. The number of spikes per square meter and grain yield showed the largest favorable relationships (r = 0.77). The circular dendrogram revealed four major clusters with distinct branch groupings related to the 81 landraces. The hierarchical clustering of the traits resulted in the formation of two large clusters. Cluster I includes days to heading and maturity. The remaining five traits are separated into two smaller groups and belong to cluster II. The first and second primary components account for 53.6% of the entire variation, with 31.1% and 22.5% of the total variation, respectively. Regarding the direct effects, grain yield was most positively impacted by the number of spikes per square meter. Grain yield was indirectly positively impacted by plant height and the number of spikes per square meter through the number of grains per spike characteristic. Conclusions Multivariate analysis is employed in the revelation of interrelationships’ correlations of traits among Egyptian barley landraces. Number of spikes per square meter and number of grains per spike were the most correlated traits influencing grain yield and, therefore, should be prioritized in breeding schemes. The findings can be used to aid the selection of high-performance genotypes for yields improvement and tolerance to stressful environments.