Association analysis based on linkage disequilibrium has become a common and powerful approach for detection of QTLs underlying complex agronomic traits including drought tolerance. To determine marker/trait association, 148 modern European spring barley cultivars were evaluated under drought stress. Associations of morphological traits with AFLP/SSR markers were investigated based on the mixed linear model using the TASSEL3.0. Population structure was estimated using various methods including Bayesian clustering model by STRUCTURE software, PCoA analysis, NJ dendrogram and Hierarchical Clustering. Linkage disequilibrium patterns were explored among the whole genome and each chromosome separately. All the analysis for population structure divided the population into two sub-groups. Linkage disequilibrium analysis showed that by increasing genetic distance, LD decreases. Totally, 167 significant marker trait associations were found which delineated into 65 QTLs in both treatments. Two stable QTLs on 5H at 86.880 cM were detected for Internode Length and on 3H at 126.421 cM for flag leaf length in drought stress treatment. Fourteen QTLs were co-localized with previously reported QTLs and others were novel. The results indicate that these putative genomic regions contain genes that have pleiotropic effects on morphological traits in drought condition.

Since in most mapping models geometric mean of different criteria are used to determine the desertification intensity, one of the most important issues in desertification studies is understanding the similar areas, which require similar management after determining the desertification intensity map. Two similar classes of desertification intensity may require different management due to differences in the criteria that affect its desertification severity. Therefore, after determining the geomorphological facies as the working units in Sistan plain, we used hierarchical cluster analysis to identify the homogeneous environmental management units (HEMUs) based on indices of MEDALUS model. According to the MEDALUS model, the studied area was divided into two categories namely medium and high desertification classes. Working units (geomorphological facies) are classified into five clusters according to HEMUs analysis based on climate, soil, vegetation, and wind erosion criteria. The first cluster (C11) include six facies with moderate and severe desertification; in all of these units the main effective factor was wind erosion, so they need the same management decisions controlling wind erosion. Two working units (1 and 4) with the same desertification severity were placed in two different clusters due to the main factors affecting each other. The results of the Mann-Whitney test showed that the value of the test statistics was 79. Also, the value of Asymp.Sig was obtained to be 0.018, which is less than 0.025 (two-tailed test), and it can be concluded that the classification of work units in the two models, clustering and desertification, is not equal (P<0.05). So It seems that using cluster analysis to identify the same units, which need the same management decision after preparing the desertification intensity, is necessary.

Association mapping (AM) has proven to be a powerful approach for dissecting the genetic basis of complex traits. In this study, Quantitative Trait Loci (QTLs) controlling flag leaf characteristics under drought stress were detected in a set of 148 modern spring barley cultivars using AM analysis. Flag leaf length (FLL), flag leaf width (FLW), relative water content (RWC), chlorophyll content, and maximum quantum efficiency of PSII (Fv/Fm) which are important in photosynthetic rate, were evaluated under normal irrigation and drought stress conditions at grain filling stage. Population structure was estimated using Structure 2.3 and linkage disequilibrium (LD) was estimated by the 'Full Matrix LD' using Tassel 5.0. Significant marker/trait associations were investigated based on K-Q matrix using Tassel 3.0. The analysis of population structure divided the cultivars into two subgroups. Significant LD values (P < 0.01) between polymorphic sites with regions of high and low LD were observed. A total of 84 significant putative genomic regions were identified, which delineated into 37 QTLs under two water treatments. Two stable QTLs on 2H and 3H were detected for FLL in drought stress treatment. A QTL for FLL were detected on 2H in normal treatment, which alone explained around 11% of phenotypic variance of FLL. This QTL was also associated with the expression of FLW and explained around 7.5% of phenotypic variance. The results suggest that major loci are located on chromosomes 2H, 3H, 4H and 5H involved in the development of flag leaf characteristics and could be used as selection criteria in barley breeding for drought tolerance.

In the present study, 148 commercial barley cultivars were assessed by 14 AFLP primer combinations and 32 SSRs primer pairs. Population structure, linkage disequilibrium, and genomic regions associated with physiological traits under drought stress were investigated. The phenotypic results showed a high level of diversity between studied cultivars. The studied barley cultivars were divided into two subgroups. Linkage disequilibrium analysis revealed that r2 values among all possible marker pairs have an average value of 0.0178. The mixed linear model procedure showed that totally, 207 loci had a significant association with investigated traits. 120 QTLs out of 207 were detected for traits under normal conditions, and 90 QTLs were detected for traits under drought stress conditions. Identified QTLs after validation and transferring to SCAR markers in the case of AFLPs can be used to develop MAS strategies for barley breeding programs. Some common markers were identified for a particular trait or some traits across normal and drought stress conditions. These markers show low interaction with environmental conditions (stable markers); therefore, selection by them for a trait under normal conditions will improve the trait value under stress conditions, too.

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