بررسی رابطۀ عملکرد دانه و صفات وابسته در ارقام کلزای بهاره با استفاده از روش‌های آماری چند متغیره

The efficiency of a breeding program depends mainly on the direction of the correlation between yield and its components and the relative importance of each component involved in contributing to seed yield. The objective of this study was to detection of traits affecting canola yield by multivariate analysis, at 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, HI and seed yield. PC2 was moderately correlated with days to flowering, days to maturity and flowering period. 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 these traits as selection criteria in breeding programs for improve seed yield of spring rapeseed cultivars.