English

Abstract

Leaf rust disease affects the wheat crop in several countries around the globe and it can influence the grain yield and its components. This research was carried out using 35 wheat genotypes during the growing season of 2016-2017 with 3 replications by RCBD under contrasting rust disease regimes. The statistical techniques used for the multivariate analyses include the calculations of correlations, principal components and clusters. The data about various physiological traits, grain yield components and disease severity were recorded under high disease pressure and maximum disease control conditions. Correlation analysis showed highly significant positive relationship of disease severity with relative membrane permeability but negative association with chlorophyll contents in the flag leaf and some yield attributes. In control conditions, the relative water content exhibited a highly significant positive relationship with the flag leaf area while highly significant negative relationship was observed with specific flag leaf weigh under disease condition. Principal component analysis demonstrated that first 4 PCs having eigenvalue >1 elucidated 73.578% and 82.80% of the total variation under diseased and control conditions respectively. Cluster analysis grouped 35 wheat genotypes among four different clusters. The members of cluster 1 revealed the maximum disease severity under control condition, but the disease severity was maximum for cluster 4 under disease condition. Scatter plot explained that, not a single cluster showed clear separation. The tree diagram also indicated that diversity in different disease conditions is controlled by genotypes. The results concluded that this genetic diversity could be helpful to the researchers and breeders for future objectives to enhance the food production and leaf resistance in bread wheat. Keywords: Wheat, Leaf rust, Multivariate analysis, Genetic diversity, Morpho-physiological traits