Journal of Crop Production and Processing

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Using multivariate statistical methods in evaluation of various traits in several genotypes has caused the discovery of different aspects of agronomic crops’ traits. In order to study diversity and interrelationships of yield and yield components of rapeseed, 36 genotypes of rapeseed were used in a 6 × 6 simple lattice design layout with two replications. Results of primary analysis of variance indicated that it was possible to analyze the dataset via randomized complete blocks design. In general, 13 traits, which were related to yield and yield components, were evaluated in this investigation. Results of dataset analysis showed that there was considerable variation among the genotypes. Seed yield of rapeseed had positive and significant correlation with 1000-seed weight, harvest index, number of secondary branches in plant and maturity period. In stepwise regression of yield with other traits, the 1000-seed weight and days to end of flowering described most of the variations of seed yield. Also, results of path analysis indicated that 1000-seed weight and days to end of flowering had direct and remarkable effect on seed yield. Cluster analysis and multivariate analysis of variance divided the genotypes into five distinct groups. Based on seed yield and 1000-seed weight, the genotypes of fifth cluster and according to highest number of pods per plant, the genotypes of third cluster were considerable. In general, the most important trait which affected seed yield of rapeseed was 1000-seed weight, which could be used for indirect selection of seed yield in segregating generations.

Keywords: Cluster analysis, Path analysis, Stepwise regression, Simple correlation.

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