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Path and correlation analysis were executed to investigate the relationships between grain yield and other important yield components in bread wheat (Triticum aestivum L.) genotypes during two years (2009)(2010)(2011) under supplemental irrigation and dryland conditions. Field experiments were performed in a randomized complete block design with four replications. Grain yield showed positive correlation with plant height and test weight under supplemental irrigation condition. The similar results were also revealed between grain yield and plant height, spike length, days to maturity, agronomic score and test weight in dryland environment. The grain yield of bread wheat in dryland condition depended on the effect of plant height, days to maturity, agronomic score and 1000 kernel weight, whereas in supplemental irrigation was mainly related to plant height, spike length, 1000 kernel weight and test weight. The influence of 1000 kernel weight on grain yield in both environments seems to cause from the fact that grain yield in wheat is frequently the sink limited, and for this reason, the 1000 kernel weight has been reported as a promising trait for increasing grain yield in wheat under different conditions. The nearly equal value of correlation and path coefficients of plant height and grain yield showed plant height had positive and direct effect on grain yield, in both conditions and suggesting a criteria trait for improving of grain yield. The results showed that genotype 12 (CS/TH.SC//3*PVN/3/MIRLO/BUC/4/MILAN/5/ TILHI) is a high yielding potential genotype in moisture limited conditions.

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SUMMARYQuick seed germination and stand establishment are significant factors to lentil This study was performed to determine the yield performances of 20 durum wheat genotypes across five sites in warm dryland areas of Iran, during 2004-2006 growing seasons. The experimental design was a randomized complete block design with four replications. The combined analysis of variance indicated that effects of environments, genotypes and genotype × environment (GE) interactions were significant, suggesting differential responses of the genotypes to environments and the need of stability analysis. Analysis of variance for AMMI (additive main effects and multiplicative interactions) model revealed the first four interaction principal components (IPC 1, IPC 2, IPC 3, IPC 4) were highly significant by Gollob's F-test and accounted for 78.32% of GE interaction. The genotypes have high variation around the mean yield (3358.68 kg ha-1). According to IPC1, genotypes G17, G3, G1 and G8 were the most stable genotypes. Based on EV4 parameter, genotypes G17, G8, G12, and G18 and according to EV1, genotypes G4, G6, G19, G7 and G20 were the most stable genotypes. Genotypes G10, G9, G4, G14, G11, G6 and G18 based on SIPC4 parameter and genotypes G8, G1, G12, G18 and G17 based on ASV parameter were the most stable genotypes. MASV indicated that G17, G12, G8, G18, G1 and G3 were most stable genotypes. Overall based on the all AMMI parameters, genotypes G3, G8, G1, G12, G17 and G18 were the most stable genotypes which had relatively high mean yield and can be used as superior genotypes in relation with the warm dryland environments.

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