For estimation and graphical analysis of genetic parameters related to plant height، yield and yield components in lentil، six parental genotypes along with 30 F2 generations derived from compete diallel crosses between them (totally 36 genotypes) were grown in a randomized complete block design with three replications at research farm of Shahre Kord University in 2012. From each experimental plot، fourty F2 and ten parental plants were randomly selected and desired characteristics were measured. Estimation of average degree of dominance and results of graphical analysis showed that gene action was of complete dominance type for plant height. However، incomplete dominance type of gene action was observed for number of pods per plant، number of seeds per plant، 100 seed weight، seed yield and number of seeds per pod. The highest amount of narrow-sense heritability (77%) was observed for 100 seed weight and number of seeds per plant and the lowest (32%) for plant height. Proportion of genes with positive and negative effects (H2/4H1) differed from 0. 25 in all traits which indicated that the frequency of positive and negative genes is not equal in the parents.

The plant genetic resources are important, because they have most valuable national basis resources in the each country. In this study, to grouping the 92 almond progenies from ‘Shahrood1’ × ‘Shahrood12’ and comparing them in terms of heritability with their parents, measured on the basis of almond universal descriptor. Principal component analysis (PCA) was used to compare 15 morphological and phonological traits among study progenies. The important traits frequency such as flowering time, tree size, resistance to frost, growth habit, flower density and leaving time in all hybrid population and compare them with their parents showed their asymmetric distribution among them. The simple correlation coefficients traits showed that among some measured traits was a significant positive correlation. In other hand, the eigenvalue variance percentage and cumulative variance showed the among measure traits, three independent factors that their eigenvalue were more than seven, they could justified 60% of total variance. Also the results of cluster analysis all cultivars were divided into three main groups. some of progenies likes ‘Shahrood1’ in third group, some other likes ‘Shahrood12’were in second group and some other that expression of phenotypic traits were additive mode, incomplete dominance or over dominance in first group.

Introduction During years genetic improvement of economically important traits, which are amongst polygenic traits, has been based on the estimation of breeding values i.e. the total heritable effects of genes, based on pedigree and phenotypic records. This approach had limitations such as being time consuming and demanding massive phenotypic information. Nowadays, high throughput genomic technologies are available that provide genotypes of dense markers across genome towards estimating breeding values more accurately. Accurate estimation of allelic and genotypic effects of markers in linkage with QTLs needs a lot of phenotypic observations which is not always available in practice. Therefore, the amount of error of estimated QTL effect could be high. Further, the distribution of the effects of genes controlling traits might be non-non-normal. In case of overlooking these facts, the predicted genetic progress can be erroneous. The objective of this study was to find the influence of the accuracy of QTL effect estimation, considering the dominance deviation, on marker assisted selection response.
Materials and Methods A base population of 1000 unrelated, non-inbred individuals was simulated according to a trait with heritability of 0.1 and 0.3. The trait was affected by residual polygenic and QTL with additive effect associated with 0.0, 0.1 and 0.2 standard errors and complete or incomplete dominance effect. The genotypic effects of the three QTL genotypes were a, d and –a, respectively for dominant homozygotes, heterozygotes and recessive homozygotes. The QTL had two alleles and the dominance deviation was considered either equal to or half of the genotypic effect a. The population was in Hardy-Weinberg equilibrium. The polygenic variance was calculated as the difference between total additive genetic variance and QTL variance. Residual variance was equal to the difference between phenotypic variance and total additive genetic variance. Two selection was employed; one with polygenes and marker information, and the other one with polygenic variance without marker information. The difference between mean of selected group and the population mean was considered as response to selection. The selection response calculated by truncation selection based on the performance of top 20% with and without using QTL information over 500 repetitions.
Results and Discussion The results showed higher response for marker assisted selection compared to conventional selection without marker information, but it also showed the presence of dominance effect for QTL effect associated with estimation errors leads to decrease in marker assisted selection response. The superiority of genetic progress with marker assisted selection is proportional to the QTL variance contributing to the total genetic variance. Increasing standard error of QTL effect to 10 and 20 percent, led to lower genetic response to selection. When the contribution of QTL variance in total genetic variance is higher, with high levels of standard error of QTL effect, the response to selection was even lower than response to selection without marker information. Complete dominance further decreased the genetic response compared to incomplete dominance. This is because the genetic variance is more influenced by the dominance variance in case of complete dominance.
Conclusion This study showed that QTL information may be used in practical selection programs when estimated parameters are of high accuracy to be used in practical selection programs. Estimating QTL effects with error causes that selection response would be even lower than polygenic selection if the associated error rate is high. Estimated effects of genes controlling quantitative traits should have less error rate in order to be used in breeding programs.

To create genetic variations in potato during four years of study (2007-11) and use than in breeding programs, some 105 hybrids were selected from cresses of Agria, Savalan, Boren, Kennebek and Ceaser cultivars as hybrids parents, and planted in augmented design at the Agricultural and Natural Resources Research Station of Ardabil during 2010-2011. The marketable tuber yields produced by the parents and hybrids were 42-52 t.ha-1 and 10.4-138.8 t.ha-1, respectively. The marketable tuber yields of hybrids exhibited 23.81% over dominance, 52.38% incomplete dominance, 13.33% reduction dominance and 10.48% interval dominance. Almost 24% of all hybrids selected produced higher marketable tuber yield than their parents. Heterosis for marketable tuber yield was found to be 58%. Based on the traits considered like marketable tuber yield, tuber uniformity, shallow eye depth, short stolon and yellow flesh and skin color, heterosis and dominancedegrees some 28 hybrids were selected. Among hybrids selected, 14 belonged to ♂Ceaser × ♀Savalan cross (021, 022, 023, 025, 026, 049, 057, 081, 087, 088, 095, 098, 0104 and 0105), four to ♂Savalan × ♀Agria cross (0500, 0502, 0503 0508), five to ♂Ceaser × ♀Agria cross (0611, 0613, 0616, 0618 and 0623) with early to mid-early maturity group, one to ♂Boren × ♀Savalan cross (0205), two to ♂Savalan × ♀Ceaser cross (0300 and 0303) and two to ♂Ceaser × ♀Kennebek cross (0401 and 0403) with mid-late maturity group.

The selection of suitable yielding maize cultivars to water deficit is one of the main objectives of the breeding programs. Therefore, selection of a suitable breeding method for better productivity from genetic potential of stress tolerance and understanding the type of controlling genes action and their inheritance is very important. In this regard, genetic analysis of some of the agronomic traits of the generations resulting from cross between corn inbred lines MO17 (Tolerant to stress) and B73(stress sensitive) including: F1,F2,F3,BC1 and BC2 along with parents in three irrigation conditions (normal, 50 and 75 millimeter evaporation from class A evaporation pan) was evaluated in 2017-2018. Experiment was conducted in each irrigation conditions in a randomized complete block design with 20 replications. The traits including grain yield per plant, biomass per plant, 1000 grain weight, ear diameter, ear weight and rows number were measured. Combined analysis revealed that there was a significant difference between the studied generations for maize agronomic traits. The results of the scaling test indicated the existence of epistatic effects for most traits such as grain yield per plant, biomass per plant and1000 grain weight under different irrigation conditions In most of the traits such as grain yield per plant, biomass per plant, row number per ear and 1000-grain weight, dominance effect was significant at 5% and 1% probability level. About rows number three-parameter model was the best fit model, in all three conditions. For most of studied traits, six parameters models were significant in different irrigation conditions, but was not significant for plant height under normal irrigation conditions and 75 mm evaporation due to maternal effects, gene association and multiple chi-square epistasis. Estimation of the dominance degree above 1 for grain yield and less than 1 for ear diameter in all three irrigation conditions  indicated that there was a phenomenon of over dominance and incomplete dominance in the control of them. High levels of genetic broad sence and narrow sence heritability suggested that genetic effects and additive effects have a greater role in the inheritance of 1000 grain weigth in all three irrigation conditions.

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.

To study the genetic control of grain yield and its components in rice using Hayman graphical method, 56 progenies obtained from diallel mating with eight parents (64 genotypes in total) were evaluated using randomized complete block design with three replications at research field of the Rice Research Institute of Iran in 2013. Agronomic traits, grain yield and its components were measured and recorded. Estimation of genetic parameters for grain yield by Hayman’s method showed that the additive variance (D) was less than the two components of dominance variance (H1) and (H2), and the average degree of dominance of genes is greater than one (1.741). Results showed that grain yield, filled grain number per panicle, 100-grain weight, panicle number per plant, and plant height were under the control of additive and non-additive effects as well as maternal and non-maternal effects. Line RI184421 (Sepidrood × Hasansaraei) and line 23 (IR75479-199-3-3) had the highest number of dominant and recessive alleles for grain yield, respectively. Plant height and panicle length was affected by the incomplete dominance effect, and grain yield, filled grain number per panicle, 100-grain weight and panicle number per plant were controlled by the overdominance effect. The broad-sense heritability of studied traits was high (˃ 90%). Narrow-sense heritability was high for plant height, indicating the importance of additive effects in the genetic control of this trait. Based on the results of this study, it is recommended that to improve grain yield and its components in rice that are controlled by the non-additive gene effects by using hybrid technology and to improve traits such as plant height and panicle length using selection based breeding methods due to the key role of additive effects in their genetic control.

The construction of molecular maps and identification of genomic regions controlling quantitative traits have great significance for plant breeders. In this study, a genetic analysis of quantitative trait loci (QTLs) affecting the heading date of rice was performed using an F2 population of a cross between two Iranian landrace cultivars, Domsephid and Gerdeh, comprising 192 plants. An approximately normal distribution was observed for the heading date in the F2 population. A genetic linkage map with 88 informative microsa-tellite markers (SSR) was constructed, which covered 1367.9 cM of the rice genome with an average distance of 18 cM between markers. Single marker analysis (SMA) and inter-val mapping (IM) procedures were used to detect the QTLs controlling heading date and QTLs identified were further confirmed using composite interval mapping (CIM). Six significant QTLs (LOD≥3.0) were identified for the heading date, of which three major QTLs mapped on chromosomes 6 (hd6), 7 (hd7) and 8 (hd8) had particularly high LOD scores and explained 23.5%, 19.8% and 20.5% of the total phenotypic variance, respec-tively. Three other minor QTLs detected for the heading date, located on chromosomes 1 (hd1), 3 (hd3) and 11 (hd11), accounted for 6.6%, 11.7% and 6.6% of the phenotypic variation, respectively. The additive effect of a single QTL ranged from 1.67 to 3.91 days. In the QTL hd6, alleles from Domsephid were responsible for reducing the heading date, while in the other five QTLs, alleles from Gerdeh caused a decrease in the heading date. The QTLs hd1, hd3 and hd8 showed over dominance effects for increasing the heading date, whereas the other three QTLs had partial to incomplete dominance effects for in-creasing (hd7 and hd11) and reducing (hd6) the heading date.

To estimate gene action and heritability of yield and yield components of maize, F2 progenies derived from half-diallel cross of five S7 maize lines along with parental lines were assessed in a randomized complete block design with three replications at the Research Farm of Graduate University of Advanced Technology, Kerman, Iran, in 2017-18. The studied traits were grain yield and its components including number of ear per plant, number of grain per ear, number of grain row, number of grain per row, ear length and 100-grain weight. Results of analysis of variance showed significant differences among genotypes for all studied traits at 1% probability level. The results of Hayman’s graphical analysis also indicated that the contribution of non-additive gene effects was more important than additive effects in controlling most traits. Number of ear, number of grain per row and grain yield per plant were controlled by the incomplete dominance effects of genes, while the other traits were controlled by over-dominance effects. Broad sence heritability of the traits varied from 0.03 for number of grain row to 0.50 for 100-grain weight. The results of this study showed that both hybrid production and selection methods can be used to breed the number of ear, number of grain per row and grain yield per plant, but to breed the other traits in the studied population, the use of heterosis phenomenon and hybrid production is suggested.

The diallel mating design is an important tool used by plant breeding programs to obtain information on trait inheritance. Knowledge of gene action, heritability and genetic advance from selection is a prerequisite for starting a breeding program for developing varieties of maize. Five maize S7 lines and their F2 progenies were studied in a 5 × 5 half-diallel crossing design to evaluate the gene action and the heritability of biochemical and physiological traits. Parents and their F2 hybrids were planted in a randomized complete block design with three replications at the Research Farm of Graduate University of Advanced Technology (Kerman, Iran) in 2017 cropping year, and chlorophyll (Chl), proline, protein, carotenoid and reducing sugars traits were evaluated. Analysis of variance showed significant differences among genotypes for the studied traits at 1% probability level. The graphical results of Haymanchr('39')s analysis showed the role of over-dominance genes effects in controlling proline content, sugars content, Chl a, Chl b, total Chl and carotenoids traits whiles the protein content trait was controlled by the incomplete dominance of genes. The narrow-sense heritability for carotenoid and proline content traits were 0.14, for protein content was 0.44 and for other traits were varaied in this range. The results of this study showed that the use of heterozygosity and the production of hybrid varieties can be used to breeding traits such as proline content, sugars content, Chl a, Chl b, total Chl and carotenoids. However, for breeding of protein content, use of both methods (selection and production of hybrid) are proposed.