Drought is one of the most important factors limiting the growth and production of crops in most parts of the world and Iran and affects as a multidimensional stress on plants at different levels. In order to study drought tolerance of durum wheat genotypes, an experiment was conducted in a randomized complete block design with three replications in stress field in Kouhdasht city. Results of analysis of variance showed that the response of the studied genotypes was different for grain yield and the possibility of selection of genotypes based on each of the traits. Comparison of numerical values and rank of each genotype according to drought tolerance indices showed that based on drought tolerance indices according to seed yield of genotypes (Omrab ), (Hana) and (Aria (stork) as drought tolerant and genotypes, Other genotypes were identified as susceptible genotypes. The results of correlation coefficients between indices showed that MP, GMP, HAM, STI indices had positive and significant correlation at probability level with grain yield in stress and non-stress conditions. There were some, so it can be said that these indices are the best indices for identifying superior genotypes. Principal component analysis results showed that the first two components accounted for about of the data variation. According to Gabriel's biplot chart, the studied genotypes were classified into two high yield potential and low yield potential areas, with genotypes (Omrab ), (Hana) and (Aria (stork) being adjacent to vectors. Drought tolerance was identified as superior genotypes. Cluster analysis based on superior indices separated the studied genotypes into three general groups, which were in good agreement with the results of Gabriel biplot plotting.

In this study 25 wheat genotypes including 22 advanced lines along with two durum (Saji and Zardak) and one bread (Sardari) wheat cultivars were grown in 19 diverisified environments in Kermanshsah, Ilam, Maragheh and Shirvan under both rainfed and supplemtary irrigation conditions during four cropping seasons (2006-2010) in Iran. The large magnitude of the GE interaction in combined-ANOVA of grain yield relative to genotypic effect, sugessted the possible existence of sub-environmental groups for the genotypes. The GGE biplot analysis showed that the cold environments were seprated from the warm environments and these two groups gave dissimilar results in ranking of genotypes. The moderate eviormnents were correlated with the both warm and cold environment groups. The genotypes G8, G17, G23 (Saji), G11, G21 and G19 could be recommended as genotypes with high yield and stability performance. The genotypes G21, G16, G8, G23 (Saji) and G17 were highly adapted to warm environments, while the genotypes G25 (Sardari), G24 (Zardak) and G6 were highly adapted to cold environments. The genotypes G20, G22 and G19 can be considered as genotypes with general adaptability.

The objective of this research was to evaluate and to quantify the magnitude of the genotype ´ environment interaction effects on mung bean grain yield and to determine the winning genotype for the test environments. Seven mung bean genotypes were tested at three locations for over two years. The grain yield data for each environment (location year combination) was first subjected to analysis of variance using generalized linear model. Mean grain yields of genotypes for the environments were computed to generate a genotype and environment two-way table data for the GGE biplot analysis. The analysis revealed the presence of significant genotype x environment interactions for grain yield. Location effect explained more than 60% of the total grain yield variation. GGE biplot analysis depicted the adaptation pattern of genotypes at different environments and discrimination ability of testing environments. MH-96-4, shown to have the potential of combining high yield with stable performance, can be recommended for production in mung bean growing ecologies in southern Ethiopia.