Volume 9, Issue 22 (9-2017)                   jcb 2017, 9(22): 53-62 | Back to browse issues page


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Ghanbari A A, Mozafari H, Hassanpour Darvishi H. (2017). Identification of Effective Traits on the Yield in bean Genotypes using Multivariate Statistical Methods. jcb. 9(22), 53-62. doi:10.29252/jcb.9.22.53
URL: http://jcb.sanru.ac.ir/article-1-842-en.html
Agronomy Dept., Shahr-e-Qods Branch, Islamic Azad University, Tehran, Iran
Abstract:   (3896 Views)
To investigate some quantitative and qualitative traits of genotypes a field study was performed as augmented experiment consisting four checks (Sadri, Koosha, KS21676 and KS21682) and138 genotypes. Vegetative, morphological and agronomical characteristics as well as traits related to pod and seed were studied. Statistical analysis showed that number of seeds per plant and plant height had the greatest variations. Genotypes had significant differences in all growth stages, yield and yield components. Correlation analysis revealed that five traits including days to emergence of the first trifoliate leaf (V3), plant height, plant type, seeds per pod and grain marketing were significantly correlated with grain yield. Five traits entered into the model based on stepwise regression analysis that were plant type, seeds per pod, grain filling duration (GFD), V3 and grain marketing. Path analysis results indicated a high direct effect of plant type on grain yield. Due to available direct effects, it was recommended seeds per pod, GFD, V3 and grain marketing for breeding programs. Overall, due to path analysis results, can be said that the characteristics plant type, seeds per pod and GFD were the most effective direct factors in grain yield variations. Factor analysis using principal component method showed that seven main factors explained more than 76% of the total variation.
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Type of Study: Research | Subject: اصلاح نباتات، بیومتری
Received: 2017/10/9 | Revised: 2019/04/15 | Accepted: 2017/10/9 | Published: 2017/10/9

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