Use of Multivariate Analysis in Determining Characteristics for Grain Yield Selection in Wheat

Abstract

Hierarchical clustering techniques have long been the most popular clustering method with Ward's method and average linkage probably being the best available (Milligan, 1980). Even though hierarchical techniques have been widely used, they do offer several distinct disadvantages that affect any of their cluster Abstract | Multivariate analysis was used to assess the diversity in 176 wheat genotypes for morpho-physiological traits. Simple correlation coefficients indicated that grain weight had a significant positive relationship with residual transpiration, osmotic adjustment, cell membrane stability, flag leaf weight, specific flag leaf weight, while negatively correlated with specific flag leaf area. These results indicated the importance of physiological traits and their positive influence on grain weight. Multivariate techniques, including factor analysis (FA) and cluster analysis, indicated that the magnitude of variability existing in the gene pool was satisfactory for initiating a breeding plan. Relative water content, cell membrane stability, osmotic adjustment and grain yield per plant were major contributors towards variability. Grain yield per plant was closely linked to relative water content, cell membrane stability and specific flag leaf area. Eight clusters were formed through cluster analysis, and greater genetic distance was detected among the members of cluster 6 and cluster 8 and cluster 7 and 8. Members of these two clusters can be utilised in transgressive breeding.