title: Determining the most effective traits to improve saffron (Crocus sativus L.) yield.
abstract: To determine the effective traits to improve saffron yield, a split plot design based on RBCD was done in Mashhad region in Iran for three years (2012-2014). The results showed that all traits except number of daughter corm, fresh weight of daughter corm and dry leaf weight had low general heritability. Results of genotypic and phenotypic coefficients of variation and genetic advance demonstrated that the majority of traits had a low diversity and the selection did not have any effect in improving the traits. As a result, the best way to increase saffron yield is improvement of farm management. It was also found that saffron yield had the highest phenotypic and genotypic correlations with fresh and dry weight of daughter corm and dry and fresh flower weight. Therefore, the efforts to improve these traits will increase saffron yield. According to the present study 5-Jun to 5-Jul was found to be the best sowing date for planting saffron. Also, the Mashhad and Torbat ecotypes were the best ecotypes in this study. Phenotypic and genotypic path analysis showed that in the first step three traits number of daughter corm, fresh flower weight and flower number and in the second step traits fresh weight of daughter corm, dry flower weight and dry leaf weight interred to the regression model and had the highest positive direct and indirect effects on saffron yield. Mainly, it can be derived that the implementation of correct farm management including appropriate sowing date, saffron ecotypes, proper density, bigger and higher quality saffron corm can play an important role in improving yield components and subsequently increasing saffron yield.
authors.affiliation: Young Researchers and Elite Club, Mashhad Branch, Islamic Azad University, Mashhad, Iran.
authors.forename: Mahdi
authors.initials: M
authors.lastname: Bayat
authors.affiliation: Department of Biotechnology, Institute of Science and High Technology and Environmental Sciences, Graduate University of Advanced Technology, End of Haft Bagh-e-Alavi Highway Knowledge Paradise, 7631133131, P.O.Box: 76315-117, Kerman, Iran.
authors.forename: Mehdi
authors.initials: M
authors.lastname: Rahimi
authors.affiliation: Young Researchers and Elite Club, Ahvaz Branch, Islamic Azad University, Ahvaz, Iran.
authors.forename: Mehdi
authors.initials: M
authors.lastname: Ramezani
keywords: Cluster analysis; Genetic advance; Heritability; Phenotypic and genotypic path analysis