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Showing 3 results for Sunflower
Fatemeh Sahranavard Azartamar, Mortaza Ghadimzadeh, Reza Darvishzadeh,
Volume 2, Issue 2 (3-2016)
Abstract
Knowledge about the amount of genetic diversity and understanding relationship between genotypes are important steps in plant germplasm conservation and breeding activities. In this study, the genetic diversity among 106 sunflower lines was assessed by 30 microsatellite primers. A total of 71 alleles were detected. Number of alleles in microssatellite loci ranged from 2 to 4 with the average number of 2.207 alleles per locus. The effective number of alleles ranged from 1.058 in locus ORS718 to 3.147 in locus HA3040. The average number of effective alleles was 1.641. The mean of PIC value was 0.344. Based on allele number and PIC value, SSR loci such as HA3040 and ORS733 are considered appropriate markers for studying genetic diversity in oily sunflower. Based on the results of cluster analysis using Jaccard's similarity coefficient and complete algorithm, the lines were grouped into four groups. Nineteen six out of 106 genotypes were grouped according to their origins (research centers). The highest and lowest Nei genetic distances were 0.21 and 0.004 between “NOVARTIS and HUNGARY” and “SPII with ENSAT and INRA-MONTPOL” groups, respectively. Analysis of the population structure revealed 5 subpopulations in the studied panel. The results show that the assignment of lines to subpopulations is not concordance with their geographical distribution pattern. The genetic diversity and distance revealed by SSR markers can be used in oily sunflower crossing and breeding programs
Khadijeh Mousa Khalifani, Reza Darvishzadeh, Masoud Abrinbana, Aram Nouri,
Volume 5, Issue 2 (3-2019)
Abstract
Sunflower (Helianthus annuus L.) is an important crop that its oil has nutritional and high economic value. Basal stem rot, caused by Sclerotinia sclerotiorum and S. minor, is one of the important and devastating disease of sunflower. The use of resistant cultivars is considered as the most important and effective method to control the disease. In this study, the reaction of 100 oily sunflower lines to three isolates of S. sclerotiorum and three isolates of S. minor was studied. Identification of gene loci associated with resistance to disease was done with markers produced with 30 SSR primers pairs. The results showed that some of sunflower genotypes had well resistant to Sclerotinia disease. Population structure analysis using Structure software identified 2 subpopulations (K=2). Association analysis using TASEEL software with general and mixed linear models (GLM and MLM) identified 14 and 12 loci, respectively that have significant association with resistant genes related to Sclerotinia. ORS617 locus was commonly related to genes associated with resistance to M1 from S. minor and J1 from S. sclerotiorum. The common markers are important in sunflower breeding programs making possible simultaneously selection for several traits and producing resistant cultivars to Sclerotinia disease.
Maryam Rasoulzadeh Aghdam, Reza Darvishzadeh, Ebrahim Sepehr, Hadi Alipour,
Volume 8, Issue 1 (8-2021)
Abstract
Nutrient deficiencies are important abiotic stresses that can affect plant growth and development. In this study, 76 sunflower pour lines collected from different regions of the world were evaluated in pot using some physiological traits with combined analysis of completely randomized design with three replications under optimal and phosphorus deficit conditions. Phosphorus deficiency decreased the means of all studied traits except canopy temperature. Oilseed sunflower lines were grouped into five and four clusters in each one of optimum and phosphorus deficient conditions, respectively. However, in both optimum and phosphorus deficient conditions, lines 19, 21, 27, 44 and 71 were classified into desirable cluster with high yield and yield components. Multivariate tolerance index (MFVD) for each genotype was calculated using the ratio and productivity matrices of the studied traits under optimal and phosphorus deficit conditions using principal component analysis on the resulting matrices. Based on the resulting biplot, lines 71, 74, 65, 21, 39, 7, 18 and 11 were introduced as desirable and phosphorus deficit tolerant lines.
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