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Showing 6 results for Regression
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.
Raheleh Aziznia, Hedieh Badakhshan, Taimoor Javadi, Soma Zamani,
Volume 6, Issue 2 (3-2020)
Abstract
In this study, variation of beta-glucan content was assessed in 20 barley line and cultivars based on complete block design with three replications. Genetic diversity of these genotypes was also evaluated using ISSR markers. Beta-glucan extracted by an enzymatic method. Significant differences were found at the level of 1% among barley genotypes for beta-glucan content. The beta glucan content was variable from 7.21 to 12.48 and, the Yosef, E94B3 and E94B17 genotypes hold the highest content of the beta-glucan. ISSR primers with average polymorphism of 66.79%, genetic diversity of 0.25 and Shannon index of 0.37 were determined as efficient markers for studying genetic diversity. The barley lines and cultivars were assigned in two distinct groups according to their genetic pedigree. On the basis of non-parametric Kruskal-Wallis, Spearman correlation, and stepwise regression analysis, nine informative primers were detected explaining highest seed’s beta-glucan content variations ranging from 24.3 to 42.4 percent. The ISSR6 (700), the combination of ISSR1+ISSR4 (1400) and IS2+ ISSR2 (1400) primers were the most informative primers for the beta-glucan content. The informative markers provide possible functional and efficient marker based selection method and, screening the barley germplasms for the highest beta-glucan content.
Abdul Karim Tahmasebi, Reza Darvishzadeh, Amir Fayaz Moghaddam, Esmaeil Gholinezhad, Hossein Abdi,
Volume 8, Issue 2 (3-2022)
Abstract
The selection of genotypes based on multiple traits is a fundamental issue and an important part of the process of plant breeding. In the present study, the efficiency of selection indices based on phenological, morphological and physiological traits was studied to improve sesame grain yield. The evaluation of 25 sesame populations was realized in a completely randomized design with 10 replications under Urmia conditions in 2017.The results showed that phenotypic and genotypic correlations between grain yield and No. of capsules per plant, No. of grains per capsule, No. of branches, leaf temperature, leaf index and biological weight were positive and significant. By regression and path analysis, the No. of capsules and No. of branches were identified as the variables of the first-order cause and biological weight, harvest index, leaf index, plant height and chlorophyll as the second-order cause variables, among which only plant height had a direct negative effect. In order to obtain selection indices, two optimal and basic methods and ten different vectors of economic values of traits were used. The vectors were based on the analysis of correlation, regression, path and broad sense heritability. The third and fourth indices, in which the first-order cause entered the model, showed high relative efficiency and in terms of these two indices, and the sesame populations with code number of 12, 17, 18 and 19 populations were identified as the most desirable populations. Finally, it is suggested that the efficiency of these selection indices be evaluated in the field
Kaveh Sadeghi, Mohammadhadi Pahlevani, Mohsen Esmeilzadeh Moghaddam, Khalil Zaynali Nezhad,
Volume 8, Issue 2 (3-2022)
Abstract
Identifying selection indices is the most important step of a breeding project that aims to improve grain yield. The definition of the selection index is usually done by evaluating the variables in multivariate statistical methods. In the present study, the relationship between grain yield and its components in bread wheat genotypes was determined by multivariate statistical methods. The experiment was conducted in a randomized complete block design with 3 replications in the research farm of Gorgan University of Agricultural Sciences and Natural Resources in the 2018-19 crop years. Ten commercial cultivars of bread wheat along with their offspring from direct and inverse crosses in a dialysis arrangement were evaluated for morphological and phenological traits, especially grain yield and its components. The results of genotypic and phenotypic correlation coefficients showed a positive and significant correlation (at 1% probability level) between grain yield and spike length, spike weight, number of fertile tillers, number of seeds per spike, number of spikes per spike, 1000-seed weight, biological yield and harvest index. Based on the results of stepwise regression analysis, biological yield, harvest index, number of grains per main spike and main spike weight were entered into the regression model, respectively, and explained a total of 98% of the variation in grain yield. Based on the results of path analysis, biological yield had the highest direct effect on grain yield. After biological yield, the most direct effect on grain yield was related to the weight of main spike. Also, by considering eigenvalues greater than one in factor analysis, 8 hidden factors were identified that explained a total of 75.18% of the data changes. In general, it can be concluded that biological yield, harvest index, number of seeds per spike and weight of spike compared to other traits can be used as appropriate indicators in breeding programs to select high-yield genotypes in field conditions. Genotypes Alo, Ehsan♂ × Gonbad♀ and Ehsan had the highest value for the studied traits, which can be used in future breeding researches.
Maryam Ghorbani, Kianoosh Cheghamirza, Saeed Abbasi, Zahra Aziziaram,
Volume 10, Issue 1 (9-2023)
Abstract
The current research was carried out to evaluate genetic diversity of 18 common bean cultivars and promising lines and to determine SSR and SCoT informative markers associated with 14 seed characteristics including the number of seeds per pod, 100 seed weight, seed length, seed width, the contents of crude protein, total soluble sugar, starch content, crude fat, iron, calcium, magnesium, zinc, uronic acid, and mineral ash. The polymorphism information content (PIC) values varied from 0.2 to 0.5 with an average of 0.39 for the SSR markers and from 0.19 to 0.42 with an average of 0.34 for the SCoT markers. The total average resolving power of SSR and SCoT markers were 1.54 and 5.34, respectively, indicating higher efficiency of SCoT markers than SSR markers for the diversity analysis. The common bean studied genotypes were clustered into three distinct groups for both markers based on the Complete Linkage method. Principal coordinate analysis (PCoA) for the SSR markers revealed that the first two principal components justified 59.05% of whole variation. For the SCoT marker, on the other hand, the fraction of variances explained by the first two principal components was equal to 25.43 indicating a better distribution of SCoT markers than SSR markers in the common bean genome. Analysis of molecular variance based on the grouping obtained from cluster analysis showed that the diversity within the group based on SSR and SCoT markers was equal to 89 and 78%, respectively. The results of regression analysis for the studied markers and the bean seed characteristics showed the existence of a significant relationships between a single marker with the several studied traits. This could indicate the association or linkage of the marker locations. Twelve out of 14 of the investigated common bean seed characteristics showed a significant relationship with at least one molecular marker.
Mohammad Zabet, Fahime Barazandeh, Alireza Samadzadeh,
Volume 10, Issue 1 (9-2023)
Abstract
To investigate the genetic structure of different sesame traits, 7 genotypes, including Ardestan, Sirjan, Fars, Sabzevar, Jiroft, Oltan and TS-3 were studied in the form of a 7 x 7 one-way diallel design in the research farm of the Faculty of Agriculture at University of Birjand during 2015-2018.The traits measured included plant height, height to the first capsule, number of auxiliary branches, number of leaves, leaf length, days to 50 % flowering, days to 90 % flowering, days to physiological maturity, number of capsules per plant, biological yield, grain yield, harvest index, number of seeds per capsule, capsule weight, capsule length, capsule width, chlorophyll a, b and total chlorophyll, oil and protein percentage.Hayman′s variance analysis showed that there were significant components a, b and b3 in all traits and components b1 and b2 in most traits. Parameters D, H1, and H2 were significant and the parameters F, h2 and E were not significant for most traits. The average degree of dominance (√H1/D) showed incomplete dominance and over dominance for all traits. The H2/(4H1) parameter was less than 0.25 in all traits except the day to 50 % flowering, suggesting that increasing and decreasing genes did not have symmetrical distribution among the parents. The parameter (√(4DH1)+F)/√(4DH1)-F ) showed symmetrical and asymmetrical distributions for the studied traits. In most of the traits, there was a dominant gene block controlling the traits. Broad sense and narrow sense heritabilities ranged 0.47-0.99 and 0.17-0.98, respectively. In general, all traits were controlled by genes with additive and dominance effects, so it is possible to select and produce hybrids in sesame. Considering that Fars, Oltan and TS-3 genotypes had the most dominant alleles, it is recommended that in future studies, attention should be paid to these three genotypes.
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