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This research was carried out to determine stable genotypes and investigate genotype × environment interaction (GE) effects on the forage yields of 24 tall fescue genotypes (Lolium arundinaceum, syn. Festuca arundinacea Schreb.) across 14 test environments (combination of year, location and moisture conditions). The GGE biplot method was used to evaluate the phenotypic stability of forage yield in the studied genotypes. The GGE biplot analysis accounted for 75% of the G + GE variation. According to GGE biplot, in terms of performance, the genotypes were divided into two groups. The first group, with more than the average yield, included G20, G24, G04, G01, G22, G14, G10, G17 and G02. The second group included the remaining genotypes with below-average performance. From the seven foreign genotypes evaluated, G10 and G22 fell in the first group and the rest were clustered in the second group. In the first group, the performance of G24 (from Semnan province) was the most variable (the least stable), whereas the G20 and G14 (both from Isfahan province) were highly stable. In the second group, except for G08 and G16, the performance of genotypes was highly stable. The genotype G20 (from Isfahan province) had superior performance under all of the test environments, suggesting that it has a broad adaptation to the diverse environments. The results obtained in this study demonstrated the efficiency of the GGE biplot technique for selecting genotypes that are stable, high yielding, and responsive.

<p class="042abstractstekst">Sorghum (<em>Sorghum bicolor</em> (L.) Moench) is the fifth important cereal considered a drought-tolerant crop. However, its reduction of grain yield considerably occurs in a shortage of water. In the current study, 10 sorghum genotypes were assessed for their grain yield under normal irrigation and water deficit irrigation. As well, the efficacy of several drought indices was evaluated for the selection of high-yield and drought-tolerant genotypes. The experiment was conducted as a split-plot considering three irrigation levels as main-plot and 10 genotypes as sub-plot. Correlation among the indices, clustering of the genotypes along with principal component analysis was employed. Yield production was significantly and positively correlated with indices MP (mean productivity), STI (stress tolerance index), GMP (geometric productivity), HM (harmonic mean), and YI (yield index) in all the irrigation levels. Therefore, these indices are more effective in the selection of high-yielding genotypes under different water conditions. Rank means of stress indices for each genotype revealed that genotype TN-04-79 in mild deficit irrigation and genotypes KGS23 and TN-04-79 in severe deficit irrigation were the most tolerant.</p>

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