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Showing 3 results for Analysis of Variance
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.
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.
Rahmatollah Karimizadeh, Tahmasp Hosseinpour, Peyman Sharifi, Jabar Alt Jafarby, Kamal Shahbazi, Kavoos Keshavarzi,
Volume 8, Issue 1 (8-2021)
Abstract
Durum wheat (Triticum turgidum L.), like most other crops, is affected by various stresses. Therefore, cultivars that, in addition to the ability to produce higher yields, can maintain their yield potential in different years and locations are considered superior cultivars. In order to obtain high-yielding and stable genotypes of durum wheat, 16 lines with two control cultivars Dehdasht and Seymareh were evaluated in four locations of Gachsaran, Gonbad, Khorramabad and Moghan based on randomized complete block design with four replications in three cropping seasons (2013-2016). Combined analysis of variance indicated a significant effect of genotype, environment and genotype by environment interaction. Genotypes G6 and G18 had the highest and lowest grain yield, respectively. Based on parametric methods, genotypes G3, G5, G15, G13 and G16 and based on non-parametric methods, genotypes G1, G3, G4, G5, G15 and G3 were the most stable genotypes. The most stable genotypes based on the total Kang sum-rank were genotypes G15, G5, G6 and G1. The Selection index of ideal genotype (SIIG) was used to integrate all indices into one index, based on which genotypes G5 and G15 were the superior genotypes with the highest SIIG index and grain yield. Based on all indices, genotypes G5 and G15 were the most stable genotype in terms of grain yield and can be used in cultivar introduction processes.
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