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Analysis of genotype × environment interaction for grain yield in rainfed durum wheat | ||
| زراعت دیم ایران | ||
| Article 1, Volume 2, Issue 2 - Serial Number 4, January 2014, Pages 1-14 PDF (1.14 M) | ||
| Document Type: Research Paper | ||
| DOI: 10.22092/idaj.2014.100185 | ||
| Authors | ||
| Reza Mohammadi* 1; Mohammad Armion2; Esmail Zadhassan3; Masoud Eskandari4 | ||
| 11- Deputy Dryland Agricultural Research Institute-Kermanshah | ||
| 2Center of Agricultural Research and Natural Resources, Ilam | ||
| 3Dryland Agricultural Research Institute | ||
| 4Center of Agricultural Research and Natural Resources, Shirvan, North Khorasan | ||
| Abstract | ||
| This research was investigated to analyze genotype × environment (GE) interaction for grain yield in durum wheat multi-environment trials (MET) conducted in dryland agricultural research stations (DARI) using GGE (G + GE interaction) biplot methodology and joint regression analysis (b + S2di). The environment, GE interaction and genotype effects were accounted for 84%, 7.7% and 2.3% of total sum of squares. The large variations due to environment effects are indicating environmental diversity that causes significant GE interaction and consequently variation in genotypic yields. Correlation analysis among environments indicated that the environment group corresponding to Maragheh and Shirvan locations (cold locations) differed from environment group corresponding to Ilam location (warm location) in genotypes ranking, whereas environments corresponding to Kermanshah location (moderate location), depending on cropping season, were correlated with the both environmental groups. Based on GGE biplot, the genotypes G21 (Saji cultivar), G11 and G16 had the high combination of yield and stability, while the genotypes G16, G4 and G13 were stable and G23 and G22 were unstable. According to joint regression analysis (JRA), genotypes G7, G18 and G17 with regression coefficients higher than unit were adapted to favorable environments, while G23 and G22 with lowest regression coefficients were adapted to unfavorable environments. Genotypes G16, G8 and G6 with lowest variance in regression deviation were among the first three most stable genotypes and genotypes G23, G1 and G2 vice versa. Genotypes G16, G5 and G18 based on JRA had a good combination of yield and stability. Based on both methods (GGE biplot and JRA) genotype G16 was identified as high yielding and stable genotype and G23 as unstable genotype with low yielding performance. The GGE biplot due to provide more information on GE interaction was a useful tool than the JRA. | ||
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