Introduction: The lack of sufficient information in the pedigree of the animals prevents the correct estimation of the breeding values. Henderson proposed a genetic grouping for a more realistic estimation of breeding values for phenotypic records in different years. For these groups, the birth year, the year that the first daughter of the male had recorded, or the year that the male animal was used for insemination were used for grouping. In fact, this grouping was considered for calculating the genetic trend over the years. The incomplete recording of the animals in the population will result in the elimination of true genetic relationships between animals. Although, these animals are considered as the base animal in the analysis, but not born at the same time, and can affect the accuracy of estimated breeding values. The available pedigree information in Iran does not have a good quality index. So that the average of pedigree completeness criterion for Iranian Holstein cows has been reported less than 0. 7. Genetic evaluation of Iranian Holstein cows with unknown parents may cause a bias in estimating genetic parameters and breeding values. The use of genetic groups in genetic analysis can partly correct the problem of animals with unknown parents. In this regard, the purpose of this study was to estimate the genetic parameters and breeding values of the production traits (milk, fat, protein) of Iranian Holstein cows with and without genetic grouping in model. Materials and Methods: In this study, the pedigree of 1555702 heads of the Iranian Holstein cattle from 14623 sires and 697940 dams that collected by Animal breeding center of Iran till 2013, were used. Production traits, including milk, fat and protein corrected for 305 days and twice milking from first to third lactation periods were used to estimate variance components and breeding values. Herds under 100 heads were not considered for analysis and for all production traits; pedigree related to animals with the record was extracted from the general pedigree using CFC software and used. For animals with unknown parents, genetic grouping was performed based on the sex and the birth year. Traits at different lactation periods analyzed with (model 2) and without (model 1) genetic grouping in the model and genetic trend was calculated. Then the accuracy of breeding values and genetic trend of traits obtained from different models were compared with each other. The Spearman rank correlation was used to investigate the change in animal ranking in a result of considering the genetic grouping. Results and Discussion: The additive genetic variance and their standard error were lower for milk, fat and protein production traits in model with genetic grouping (model 21) than the model without genetic grouping (model 1). The estimated heritability range for milk, fat and protein production in three lactation periods with model 1 was 0. 094-0. 162, 0. 069-0. 114, and 0. 079-0. 123, respectively, that these values were higher than model 21 in terms of magnitude. Spearman rank correlation between the estimated breeding values with model 1 and 21 was significantly different from 1, indicating a change in animal rank with consideration of genetic grouping in the model. The spearman rank correlation was lower for males than females, suggesting a higher change in male animal's rank than females. The average accuracy estimated breeding values with model 21 was higher than model 1 and the average accuracy difference was significant between two models. The genetic trend in the first, second and third lactation periods with the model 21 was estimated 63. 06, 59. 60 and 44. 64 for milk production, 1. 346, 1. 095 and 0. 943 for fat and 1. 542, 1. 514 and 1. 035 kg per year for protein, which were higher than the estimates of model 1. Conclusion: The results showed that consideration of genetic grouping in the model reduced the additive genetic variances of traits and the heritability estimated were higher without consideration of genetic grouping. The significance of the Spearman rank correlation indicates that the rank of males and females changed by inserting genetic groups into the model and change in the animal's rank for males was higher than females. The high accuracy of estimated breeding values and the genetic trends of traits in the model with genetic grouping suggests that genetic grouping for animals with unknown parents has been done and entered into the model in order to more accurately estimate the breeding values and to better reflect the performance of the breeding programs.

IntroductionCrop yield products reduction due to abiotic stress is estimated at 51 to 82%. Most plants are exposed to environmental stresses, and water deficit is one of the most important non-abiotic stresses in limiting and producing crops around the world, especially in arid and semi-arid regions. Plants have developed various strategies to cope with water deficit stress, including morpho-physiological and biochemical.Wheat is one of the most important crops in the world, which in 2020 had the highest area under cultivation at the rate of 221.33 million hectares (with a total production of 766.03 million tons) worldwide. In the same year in Iran, the area under wheat cultivation was 6.70 million hectares and its production was 16.75 million tons.Materials and methodsThe research was performed in research farm of Rainfed Agricultural Research Station Gachsaran, Iran, over 2020-2021 cropping years. In this study, 100 lines obtained from the landrace bread wheat of different origins from several continents and several countries were studied. The experiment was performed in a simple lattice design 10×10 with two replications and separately in two environmental conditions of stress and non-stress. The operation planting is done in January after conventional tillage implementation of the area by hand. The source of moisture supply for both rain fed (water deficit stress) and irrigation (no stress) test conditions was rainfall and sprinkler irrigation before the phonological stage of flowering (pollination (Zadocs scale 61)). Irrigation interruption was applied at the beginning of flowering in a stress environment (water deficit stress conditions) which continued until harvest, but the environment without stress in two times when wheat plants to early reproductive stage, flowering stages, and the beginning of grain filling (Grain paste stage (Zadocs scale 61-83)) Irrigation was performed. In this study, 16 morphological traits and grain yield were measured under both stress and non-stress conditions, including flag leaf length and width (cm), flag leaf pod length (cm), and flag leaf area (cm2), number of nodes and leaves per stem, internodes number, peduncle length (cm), plant height (cm), tiller number, fertile and infertile tillers of number, length of awn (cm), spike length (cm) and spike yield (g).Results and discussionThe results of the analysis of variance showed high and significant variability in both non-stress and deficit water stress. TRI 3492 was the most tolerant of geographical origin in Nepal and TRI 4549 had the lowest STI relative to deficit water stress of geographical origin in China. The highest and lowest heritability in stress conditions were related to plant height (98.02%) and the number of intermediate nodes (25.00%), respectively. The greatest decrease in heritability (66%) due to stress conditions was the leaf sheath length of the flag leaf. Among the traits studied in this study, flag leaf area with 31.41%, flag leaf length with 25.25% and grain yield with 23.53% had the highest percentage of stress reduction. The results of cluster analysis of the studied genotypes in both environmental conditions are in six separate and different groups so that the greatest difference in genetic distance and grain yield in both environmental conditions was observed between the first and sixth clusters.ConclusionUsing the genotypes of first cluster (TRI 403, TRI 4013, TRI 3981, TRI 10340, TRI 5262, TRI 4549, TRI 2513, TRI 2656, TRI 3477, TRI 3242, TRI 3526, TRI 3513, TRI 4116 and TRI 4113) with 6TH cluster (TRI 10296, TRI657, TRI755, TRI752, TRI757, TRI 11020, TRI691, TRI 6129 and TRI754) Can be used in crossbreeding programs as well as genetic studies (such as recombinant populations and association mapping) and to increase the rate of heterosis used in water-deficit stress conditions.

Since the production of maize hybrids needs to selection and crossing of desirable inbred lines, identification of lines with suitable genetic characteristics is one of the objectives of plant breeders. In this study, ISSR markers were used to assess genetic diversity in 100 inbred lines of maize. Sixteen primers amplified 81 loci, of which 78 (95. 12 %) were polymorphic. The maximum and minimum number of polymorphic bands were produced by UBC825 (8 loci) and UBC811 (2 loci) primers, respectively. The polymorphic information content (PIC) ranged from 0. 65 (UBC849) to 0. 93 (443), with an average of 0. 77. Cluster analysis based on Jaccard’ s similarity coefficient and complete linkage algorithm categorized the studied lines into 3 main clusters. The analysis of molecular variance using ISSR data showed that 9% of the variation was explained by the variation among population and 91% by the variation within population. The results showed that the ISSR markers capable to display a high degree of polymorphism among lines and are useful tools for fingerprinting and categorizing of maize genotypes into different groups. This feature can be used in determining heterotic groups and prediction of heterosis in maize hybrid production.

Among prokaryotes, there are certain soil bacteria known as rhizobacteria which are very significant owing to their N2 fixation ability in legumes. The nucleotide sequence of the intergenic spacer (IGS) fragments residing between the 16S and 23S rRNA genes (16S-23S IGS) are not very conserved and thus are very useful in the grouping of rhizobial strains. In this research, 52 superior plant growth promoting rhizobacteria (PGPR) were grouped based on 16S-23S IGS PCR-RFLP and plasmid profiles. The results showed that the 16S- 23S IGS fragments of different rhizobial strains vary in size (600-1486 bp) and the number of IGS copies (1-3 copies). Based on the 16S-23S IGS PCR-RFLP profiles all 52 strains were located in 48 groups with 11 groups showing 70% intraspecies similarity. By using the above method, 77% of the strains (except 12 strains Bj 53, Bj 54; Rlv 27, Rlv 28, Rlv 23, Rlv 24; Rlp 16, Rlp 17; Sm 10, Sm 11, Sm 12 and Sm13) were separated into different groups. Therefore, this simple method which possesses minimal lab requirements is highly reliable and applicable for the genetic grouping of rhizobacteria in comparison to other molecular methods. The grouping based on the plasmid profile of rhizobial strains was in agreement (to some extent) with the results of the 16S-23S IGS PCR-RFLP method. For example, grouping of the Bj 53, Bj 54; Rlv 23, Rlv 24; Rlp 16, Rlp 17 and Sm 11, Sm 12 and Sm13 strains in both methods were completely similar and located in separate cluster groups.

Licorice (Glycyrrhiza glabra L. ) is one of the oldest and most important medicinal plants in Fabaceae, used for curing many diseases since 4000 years ago. This study was conducted to evaluate the genetic diversity of 22 different licorice populations based on morphological and yield traits at the research field of the Faculty of Agriculture, Zanjan University, during 2016 to 2018. Morphological and yield traits including plant height and width, leaf length and width, number, length and width of leaflets, number of lateral branches, main stem diameter, aerial parts fresh and dry weight, root fresh and dry weight, root to aerial parts ratio and aerial parts and root yields (per m2) were measured. Canonical discriminant (CDA) and cluster (CA) analyses were used to group the populations. In CDA, the first two canonical variables were significant. The first canonical variable included plant height and width, main stem diameter, leaf length and the number of leaflets, and the second one included aerial parts fresh and dry weight, root fresh and dry weight, root and aerial parts yields. The second canonical variable had the greatest role in population separation and grouping. Canonical variables divided populations into four main groups and confirmed CA clustering results. In general, the results indicated the good potential of canonical discriminant analysis in evaluating the genetic diversity and identifying the index traits in licorice.

Background and objectives: The accuracy of estimates of variance and covariance components is a prerequisite for designing breeding strategies of important economic traits such as reproductive traits. Genetic grouping was suggested to predict breeding values of phenotypic records in different years with high accuracy. As there is unknown information in the pedigree of Holstein dairy cows in Iran, genetic group animal models with unknown parents seem necessary. Therefore, the present study was conducted to estimate the genetic parameters, genetic trend, and accuracy of estimated breeding values of some reproductive traits (i. e. calving to first service (CTFS), first service to conception (FSTC) and calving interval (CI)) in dairy cows considering genetic grouping for animals with unknown parents. Materials and methods: Information on calving and insemination dates of the first three calving periods from 3361 herds of the Iranian Holstein, collected by the Animal Breeding Center of Iran from 1981 to 2013 was used. Animals with unknown parents were grouped based on the year of birth and sex and the traits were analyzed using two models, with (model 2) or without genetic grouping (model 1). The model with the lowest Bayesian information criterion (BIC) and the Akaic information criterion (AIC) was considered the best model. Spearman's rank correlation coefficient was used to examine changes in animal rank by considering the genetic grouping. The accuracy of breeding values and genetic trends were estimated and compared using two models. Data preparation and statistical analysis were performed using R-software and ASReml software, respectively. Results: The amount of variance and the cumulative genetic standard error were lower in model 2 compared to model 1 while it was the opposite for the residual variance, however, there was no significant difference between the values of the two models. Model 2 was selected as the best model for all studied traits based on the goodness of fit criteria. The heritability of CI and CTFS was estimated to be lower (nonsignificant) in model 2 compared to model 1. The heritability values were estimated less than 0. 05 for all reproductive traits within the two models. The ranking of the best males and females changed due to genetic grouping. The accuracy of estimated breeding values (EBVs) for all studied traits was significantly (P <0. 001) higher in model 2 when compared to model 1. The genetic trend of all traits (with the exception of the FSTC in the first and third calving period) was positive in both models 1 and 2, and the estimated values were different between the two models. Conclusion: The results from the current study showed that genetic grouping is necessary to analyze the reproductive traits of Iranian Holstein cows as well as accurately predict the genetic merit of animals.

The genetic variations of 17 ecotypes of sand plantain were evaluated by 12 ISSR markers and nine morphological traits. Analysis of variance showed high variability among studied cultivars. Cluster analysis could put 17 different ecotypes of sand plantain into the three groups using UPGMA method based on field data. The assessment of ecotypes based molecular markers showed that the 12 primers could be amplified 91 polymorphic bands, the maximum number (14) was produced by UBC814 and primers UBC811, UBC813 and UBC817 with 13 bands were in the next steps respectively. The minimum band number (7) was produced by UBC824 and UBC876 respectively. PIC value was varied from 0.27 to 0.44 and MI was 0.91 to 4.10. Cluster analysis using UPGMA based molecular markers, placed 39 ecotypes in the study in five groups, include 3, 9, 3, 1 and 1 ecotypes respectively. Grouping of ecotypes with molecular markers is moderate matched with classification of the ecotypes based morphological traits.

Among prokaryotes, there are some soil bacteria called Rhizobia that are very important owing to their N2 fixation ability in legumes. The sequence between two 168 and 238 fragments of rDNA genes complex is called 16S- 23S rDNA IGS. It differs by size and nucleotide order, therefore, it is very useful for grouping of rhizobial strains. In this research 16S-23S IGS PCRRFLP and Plasmid Profile (modified Eckhardt method) grouped 52 superior strains which were found as plant growth promoting Rhizobacteria (PGPR). For cluster analysis, phylip version 3.6a3 software was used. The results show that the16S-23S IGS fragments of different rhizobial strains are very diversified in terms of size (600.,1486 bp), and the number of IGS fragment differs from 1 to 3 copies. Based on 16S-23S IGS PCR-RFLP method, all 52 rhizobial strains were located in 46 groups, of which 11 groups had 70% similarity. By this method all strains (77%) except 12 strains (Bj53, Bj54; Rlv27, Rlv28; Rlv23, Rlv24; Rlp16, Rlp17; Sm10, Sm11, Sm12, and Sm13) were separated into different groups. Therefore, the mentioned method is very reliable and practical, besides being simple and having few laboratory requirements (in comparison with other molecular methods). In this research, The grouping based on Plasmid Profile of different rhizobial strains agrees with the results of IGS-RFLP to some extent, for example: Bj53, Bj54; Rlv23, Rlv24 also Rlpl6, Rlp17 and Sm11, Sm12, 5mB in both methods were completely similar and were located in separate cluster groups.