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Introduction and Objectives: The evaluation of the genotype × environment interaction effect provides valuable information regarding the yield of plant cultivars in different environments and plays an important role in evaluating the stability of the yield of breeding cultivars. Genotype × environment interaction effect, especially in stressful environments, are important limiting factors in the introduction of new cultivars; therefore, it is very important to know the type and nature of the interaction effect and reach the verities that have the least role in creating interaction effects. Various methods have been introduced to evaluate the interaction effect, each of which examines the nature of the interaction effect from a specific point of view. The results of different methods may not be the same, but the best result is obtained when a genotype with different evaluation methods shows similar results in terms of stability. The purpose of this research was to evaluate the genotype × environment interaction effect in experiments conducted in different environments, to determine the relationships between genotypes and environments and to introduce the most stable red bean genotypes. Material and Methods: In this research, 14 red bean lines along with Yakut, Ofog and Dadfar control cultivars were cultivated in the form of a randomized complete block design with three replications in Khomein, Borujerd, Shahrekord and Zanjan research stations for 2 crop years under the same conditions. After combined variance analysis, according to the significance of genotype × environment interaction, AMMI and GGE-Biplot analysis methods were used to determine the compatibility and stability of genotypes. After AMMI Analysis, the stability parameters of AMMI were calculated. In addition to the AMMI stability parameters, the simultaneous selection index was also calculated for each of the indices, which was the sum of the rank of the genotypes based on each of the AMMI stability indices and the average seed yield rank of the genotypes in all environments. Results: The significance of the double and triple interaction effects of genotype with year and place (environment) in this study showed that genotypes showed different responses in different environments, and in other words, the difference between genotypes is not the same from one environment to another, and in these conditions, the stability of grain yield can be evaluated. The contribution of about 2.5 times the interaction effect of genotype × environment from the total sum of squares, compared to the effect of genotype, indicated the possibility of the existence of megaenvironmental groups in which some genotypes show their maximum performance potential in those environmental groups. Genotypes G12, G5 and G17 had the highest seed yield among the genotypes with yields of 3288, 3136 and 3111 kg per hectare, respectively. AMMI analysis showed that the first to seventh main components were significant at the 1% probability level, and despite the significance of all model components, the first and second main components had the largest contribution to the expression of genotype × environment interaction (66.5%). Based on AMMI1 biplot Genotypes G4, G5, G16, G17 and G12 had the highest values (positive and negative) of IPCA1. In contrast, genotypes G8, G3, G2, G7 and G11 had IPCA1 values close to zero. However, only the genotype G11 showed a performance higher than the average total yield and therefore it can be introduced as a stable genotype with high general compatibility. Based on AMMI2 biplot, genotypes G2, G7, G3 and to some extent G8 and G13 were introduced as stable genotypes, but only G13 genotype had a higher yield in all environments, so this genotype can be introduced as a stable genotype with good yield.; also, every two years, the same place under investigation had a high correlation with each other, so that Bro1 and Bro2 environments on the one hand and Kho1 and Kho2 environments and finally Zan1 and Zan2 showed a high positive correlation (the same effect) to create a mutual effect. In total of the simultaneous selection indices calculated based on AMMI analysis, genotypes G11, G17, G7, G13 and G12 were introduced as stable genotypes with high yield. GGE-Biplot analysis based on average yield and stability showed that genotypes G1, G2, G3, G8 and G7 had the highest general stability compared to other genotypes despite having the lowest yield. On the other hand, G12, G5 and G17 genotypes had the highest yield with less stability. No ideal environment was observed. But Kho1, Kho2 and Sha1 environments are closer to the ideal environment than other environments and they can be used to distinguish the studied genotypes to some extent. On the other hand, G12 genotype can be considered as a desirable genotype that has high average yield and high yield stability. In the same way, G17, G5 and G11 genotypes were in the next stage compared to the ideal genotype and to some extent they can also be considered as desirable genotypes. Conclusion: According to all the results, G12 genotype can be considered as a desirable genotype that has a high average yield and also has yield stability, and G17, G5 and G11 genotypes were in the next stage. [ABSTRACT FROM AUTHOR]

Background and objectives Changing the use of natural ecosystems, including dam construction and also the conversion of pasture land to agricultural land, can cause irreparable damage to different parts of the ecosystem. Based on the research results the most destructive of them is the reduction of vegetation, the increase of erosion and also the reduction of biodiversity. In the management of natural ecosystems, monitoring vegetation changes is very important. The present research was carried out with the aim of investigating the changes in the vegetation cover indices and species diversity in the plowed and abandoned agricultural lands and the natural cover of the pastures around the Yan Chashmeh underground dam located in Ben city of Chaharmahal and Bakhtiari province. Methodology To carry out this research, four sites including natural pastures around the dam, lands upstream of the dam (rain fields under cultivation), lands where the dam reservoir is being built (plowed and abandoned for less than 7 years) and lands downstream of cedars have been planted for more than 15 years) were selected and in each of the sites, three transects with a length of 50 meters parallel to each other and perpendicular to the slope of the area were established at a distance of 50 meters from each other. 15 plots of 2 x 2 square meters were placed on the transects with a distance of ten meters from each other. And then, in each plot, the percentage of canopy cover, biomass, percentage density of leaf litter and bare soil were recorded. The theoretical estimation method was used to determine the level of plant canopy in the plots. The biomass of the species was determined using the cutting and weighing method. In order to check species diversity, Simpson and Shannon-Wiener indices and to compare species richness, Margalf and Menhinik indices were calculated in Past software. Determining the condition of the pasture was done using two modified four-factor and six-factor methods. Results The results showed that plowing and changing the use of pasture land to agricultural land has caused a significant reduction in the crown cover and, as a result, a decrease in the amount of biomass density, and also a decrease in diversity and species richness in the plowed and abandoned lands compared to the sloping pastures of the region. The results showed that in addition to reducing the cover, plowing has caused a change in the species composition and an increase in annual and invasive species and a decrease in shrub species. According to the results of the change of pasture use, the surrounding pastures decreased from average to weak and very weak condition in plowed and cultivated pastures (upstream) with a negative trend. Conclusion The measures taken to build the dam and then the expansion of agriculture have caused plowing and soil manipulation in the region. Besides, it is possible that in the long term, abandoning agriculture due to the drop in the water level of the underground dam will cause more soil erosion. Therefore, it is necessary to continuously monitor the vegetation changes in the area of dam construction in the coming years. [ABSTRACT FROM AUTHOR]