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Showing 5 results for Akbarpour
Omidali Akbarpour,
Volume 4, Issue 1 (9-2017)
Abstract
To conduct any breeding program, understanding of the genetic structure of traits and effect of environment and genetic by environment interaction as well as effects of random or fixed in the analysis of results is essential. Subsequently, analysis of variances and variance components are important in plant and animal breeding. The ANOVA is one of the best estimators for variance components. But this estimator is not preferred to maximum likelihood (ML) and Restricted Maximum Likelihood (REML) methods when variance components are negatively estimated and unbalanced datasets arise. Therefore, the objective of this research is a review of comparison of estimates of variance components using ANOVA, ML and REML method in linear mixed models using experimental data.
Mitra Shahbazi, Farhad Nazarian-Firouzabadi, Omid Ali Akbarpour,
Volume 5, Issue 1 (9-2018)
Abstract
Chrysanthemum (Chrysanthemum morifolium) is one of the most important ornamental plants which plays a significant role in the development of gardening industry in the world. The knowledge of genetic diversity is one of the prerequisite criteria for Chrysanthemum breeding with important economic goals. Molecular markers have a significant share in elucidation of inter and intra species genetic diversity. To this end, genetic diversity of a number of Iranian cultivars was molecularly investigated by sequencing a part of rDNA, using ITS4 and ITS5 primers. Genetic distance between Chrysanthemum cultivars ranged from 0.05 to 10.15, demonstrating the power of ITS region in revealing the genetic diversity among cultivars of morifolium, suggesting Iranian cultivars have been genetically improved from morifolium species. Genetic diversity assessment of Iranian Chrysanthemum cultivars demonstrated that presumably inter, intra species or even inter population hybridization may have been involved in creating enormous genetic diversity among Chrysanthemum cultivars.
Saman Valizadeh, Ahmad Ismaili, Hadi Ahmadi, Omid Ali Akbarpour, Bijan Bajalan, Ashkboos Amini,
Volume 6, Issue 2 (3-2020)
Abstract
Wheat is mostly cultivated at rainfed condition in Iran, so, water deficit stress has much effect on yield reduction. Hence, breeding activities are necessary for introduction of wheat tolerant genotypes to water deficit stress. In order to estimate the heritability and genetic correlation between traits of 36 wheat genotypes, an experiment was conducted in two separate conditions (water stress and non-stress) based on a randomized complete blocks design with three replications. Studied traits in wheat genotypes under water stress and normal condition showed significant differences for environment, genotype and genotype× environment interaction at 1 and 5% level of probability. The results of the factor analysis showed that the 6 first factor in normal condition explained 81.13% of total variance, and the 5 first factor in stress condition explained 74.96% of total variance. Estimation of genetic correlations based on REML approach revealed that biological yield, harvest index and number of grains per spike had the highest correlation with grain yield and these characteristics are of important for selecting the varieties with high yield under non-stress and stress conditions. Estimation of heritability based on REML approach showed that number of days to heading had the highest amount of heritability in both normal and stress conditions.
Samaneh Akbari, Omidali Akbarpour, Payam Pezeshkpour,
Volume 8, Issue 1 (8-2021)
Abstract
The challenge of the interaction of genotype × environment is one of the main issues in plant breeding. Various statistical methods to estimate the interaction of genotype × environment and choice the stable and productive genotype(s) have been introduced. In this study, 14 lentil genotypes along with two controls (Sepehr and Gachsaran cultivars) were evaluated during four growing seasons (2016-2020). The experiments were conducted in a randomized complete blocks design in three replications at Sarab Changai Agricultural Research Station, Khorammabad (Iran). The combined analysis of variance was used to investigate the interaction of genotype × environment, and results of the analysis showed significant effects for genotype, year, and genotype × environment interaction. Genotypes G5 (FLIP2014-032L) and G12 (ILL8006) were introduced based on Si(1), Si(2), and NPi(1) statistics as stable and high-yielding genotypes. Based on various non-parametric statistics, genotypes G5 (FLIP2014-032L) with a mean grain yield of 1574.68 kg.ha-1 and G12 (ILL8006) with a mean grain yield of 1333.6 kg.ha-1 were introduced as stable genotypes. The heritability rate was estimated on the plot mean basis for yield trait in four years (0.61 ± 0.18) which indicated the capability of the studied genotypes to be selected and improved for grain yield. Based on the results of cluster analysis, the genotypes were divided into three main clusters. The highest distance was observed between the second and third groups. The first cluster included highly stable genotypes.
Seyedeh Somayeh Mousavi, Omidali Akbarpour, Dr Tahmasb Hosseinpour,
Volume 10, Issue 1 (9-2023)
Abstract
In this research, 15 bread wheat genotypes along with Aftab variety as a control variety were implemented with 4 replications in the form of randomized complete block design for 3 crop years (2016-2019) at Sarab Chengai Station in Khorramabad. The likelihood ratio test (LRT) showed that the genotype-year interaction effect was significant for grain yield. Based on this, singular value analysis (SVD) was performed on the matrix of best linear unbiased predictions (BLUP) of genotype × year interaction to evaluate the stability of genotypes. The scree plot showed that the first principal component accounted for 71.7% and the second principal component accounted for 28.3% of the matrix changes resulting from the best unbiased predictions of the genotype interaction per year. The biplot of the first principal component of the environment against the nominal yield also showed that genotypes No. 9, 12 and 13 had a negligible contribution to the genotype × year interaction and had higher general stability. Also, the biplot of grain yield against the weighted average of absolute scores (WAASB) placed the genotypes in four regions, so that genotypes No. 15, 16, 12, 11, and 10 are in the fourth region due to high stability (low values WAASB) and magnitude of response variable (high performance) were identified as superior genotypes. The WAASBY index (weighted average of WAASB stability and performance) identified genotypes No. 15, 16, 12, 10, 11, 14, 9 and 4 as stable and high yielding genotypes. In general, based on WAASB and WAASBY indices and their comparison, genotypes 15, 16, 12, 11 and 10 were selected as the best genotypes that can be recommended for cultivation in similar climates.
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