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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.

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Genotype×environment interactions (GEIs) can affect breeding programs because they often complicate the evaluation and selection of superior genotypes. This drawback can be reduced by gaining insights into GEI processes and genotype adaptation. The objectives of this research were to evaluate: (1) the yield stability of promising wheat lines across locations and (2) the relationship among the test environments for selecting superior lines within the cold climate mega-environments of Iran. A total of 35 wheat promising lines were grown at 7 locations during the 2008-2009 cropping season. Combined analysis of variance showed that the environment (E) accounted for 75.7% of the model sum of squares. The magnitude of the GEI sum of squares was about three times larger than that for genotypes. To determine the effects of GEI on yields, the data were subjected to the additive main effects and multiplicative interaction (AMMI) and genotype+(genotype×environment) interaction (GGE) biplot analysis. The AMMI1 model was found to explain up to 88% of the main and interaction effects. According to the AMMI1 and GGE biplots, the lines G5 and G4 were found to produce high and stable yields across environments. There were three mega-environments (Euromieh and Ardebil as mega-environment I, Mashhad, Arak, Hamedan and Jolgerokh as mega-environment II, and Karaj as mega-environment III) according to the site regression genotype (SREG) GGE model. Application of AMMI and GGE biplots facilitated visual comparison and identification of superior genotypes for each target set of environments.

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This study was aimed to assess the effects of excess boron on 59 genetically divergent wheat accessions and to identify those with high and stable yields under a range of soil boron concentrations. The second aim was to test the applicability of a laboratory technique performed at juvenile stages of development in estimating field boron tolerance. The study comprised a control and three boron treatments, applied as 50, 100 and 150 mg boric acid L^-1 in laboratory, and 33.0, 67.0 and 133.0 kg boric acid ha^-1 in field trial. Yield performance and stability were evaluated using biplots from sites regression model, while interrelationships among analyzed parameters were assessed using path coefficient analysis. Parameters were mostly decreased by excess boron when compared to the control (seedling root length, seedling dry weight, grain number per spike, grain yield, flag leaf area, leaf area duration and grain weight). Significant increase was noted for seedling boron concentration and content, percentage of sterile spikelets per spike and number of spikes per m². Spike length, number of spikelets per spike, and anthesis date remained unaffected. The majority of accessions with high and stable yields were of local origin, so, we conclude that adaptation to environmental factors other than elevated soil boron plays an important role in overall field boron tolerance. The effects of excessive external boron on boron accumulation noted at the seedling stage in laboratory studies corresponded to its effects on yield in field.

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Dry bean landraces could be cultivated under Low-Input (LI) farming conditions because of their yield stability and quality traits. The objective of this research was to evaluate and identify landraces with high yield and stable performance under LI environment and study the relationships among agronomical, physiochemical, and quality traits. Seven landraces of common bean (Phaseolus vulgaris L.) were evaluated in field trials under certified organic management during three consecutive growing seasons (2008-2010) at two different areas located in northern Greece in a RCBD with four replicates. Site per year was considered as one environment. A ranking of landraces according to seed yield potential indicated a group of five high yielding landraces, while Genetic Coefficient of Variation (GCV) for seed yield (9.80%) and number of pods/plant (9.57%) indicated useful genetic variability within landraces, combined with high heritability values (H²= 0.71 and 0.95, respectively). GGE biplot analysis for yield performance and stability indicated that landrace Kastoria fell within the scope of an ideal genotype, followed by three other promising landraces. Significant positive correlation was detected between cooking time and Ash (0.94**). High GCV values for hydration increase (16.77%) and cooking time (15.65%) combined with their high heritability (H²= 0.98 and 0.89, respectively) are of great interest for further genetic advancement. These results indicate that dry bean landraces may provide the appropriate differentiation in several important traits when cultivated under LI conditions, so, effort should be directed to exploit this variability for the development of new varieties suitable for LI agriculture.

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There are contrasting reports on the relationship between production and drought tolerance of crops with root structure. The presented research aimed to evaluate grain yield and root-related traits (in two depths) under optimal and drought stress conditions and assess the effect of root-related traits on grain yield and drought tolerance in cultivated barley (Hordeum vulgare ssp. vulgare) and wild barley (H. vulgare ssp. spontaneum). In this experiment, 30 barley genotypes were evaluated in pot culture experiment for root traits and in the field for grain yield and drought tolerance for two consecutive years. The results indicated that the genotypes with high root dry weight, area, volume and length and root to shoot ratio in depth 0-30 cm have also high value of these root traits under the depth of 30-60 cm. In this study, the root system size increased when the plants imposed to drought stress, and the level of increase was higher in the deeper soil layer. The wild barley genotypes Hsp06, Hsp74 and Hsp79 had high averages of the root dry weight, area, volume and length under both water environments. The results of farm experiment indicated that the genotypes from cultivated barley mostly have higher yield potential; however, the wild barley genotypes mainly have more yield stability under drought stress environment. The wild barley Hsp71 was identified with both high yield potential and stability under drought stress. Root dry weight and root to shoot ratio were negatively correlated with grain yield under control conditions. Under stress condition, root area, length and volume were positively correlated with yield stability index. Results indicated that the vigorous root system is not necessarily related to higher grain yield in barley; however, higher yield stability under stress environment is highly related.