Multivariate analysis of the grain yield and related traits in spring rapeseed

This experiment was conducted to investigate the identify traits explaining yield variation, recognize relationships between traits and classify accessions in spring rapeseed, at Dezful, Khozestan Province Iran,  in the agricultural year in 2015–2016. A randomized complete block design with four replications was used. The results of stepwise regression analysis revealed that 1000-grain weight, number of pods per plant, HI and days to maturity significantly had more important effects respectively on seed yield. The results of path analysis indicated that the number of grain per pod and 1000-grain weight had the largest direct effects on the grain yield. According to the results of the principal component analysis, PC1 was moderately correlated with number of seeds per pod, 1000-seed weight and seed yield. PC2 was moderately correlated with days to flowering, days to maturity and plant height. The results of factor analysis exhibited two factors including sink factor (number of seeds per pod, 1000-seed weight and seed yield) and fixed capital factor (phonological traits). It seems that its seams possible to use their traits as a selection criteria in breeding programs for improve seed yield of spring rapeseed cultivars. using WARD method cluster analysis revealed five groups and there was highest genetic distance between 1 and 5 groups, thus predict that hybridization of between 1 and 5 groups could provide best hybrids and supply a desirable genetic diversity in segregated generations for breeding programs.