gh. lotfi ayeneh

In this study LG (location-grouping) biplot analysis, as a new method, was used to identify repeatable and unrepeatable GEI patterns and to delineate mega-environments using grain yield data of five multi-environment bread wheat trials from six southern warm and dry agro-climatic zone of Iran including Khorramabad (KHR), Darab (DAR), Dezful (DEZ), Iranshahr (ISH), Ahvaz (AHV) and Zabol (ZAB). The trials included 18, 32, 28, 28 and 28 elite bread wheat genotypes. Each of genotype sets was evaluated in two successive cropping seasons of 2012-14, 2013-15, 2014-16, 2015-17 and 2016-18, respectively. The highest (7.99 ton ha-1) and lowest (4.33 ton ha-1) grand mean of testing locations across ten trials were observed in KHR and AHV, respectively. Results of the yearly GGE biplots based on the grain yield data from the 2012-13 to 2016-18 cropping seasons of 10 bread wheat yield trials across six locations varied from cropping cycle to cropping cycle, thus it was difficult to extract the common patterns across cropping seasons and grouping the test locations using two-year grain yield data. When these datasets were incorporated in a LG biplot analysis, six locations were divided into four MEs. The LG biplot explained 49.86% of the total variation of the two-way correlation table. KHR ZAB locations formed ME1 and ME2, respectively. AHV and Iranshahr ISH formed ME3, while DAR and DEZ grouped in ME4. Unlike ME1 and ME2, which had negative correlation with each other and with other MEs, ME3 and ME4 were weakly correlated, therefore, a genotype with the highest grain yield in ME3 may perform well in ME2, and vice versa. Result of this study can help bread wheat breeders to understand the bread wheat growing MEs in the southern warm and dry agro-climatic zone of Iran, and lead to better decision-making for the analysis of multi-environments yield trial data and to identify and release high-yielding bread wheat cultivars adapted to each ME.

Additive main effects and multiplicative interactions (AMMI) and genotype (G) main effect plus genotype × environment interaction (GEI) GGE biplot models were used to dissect GEI interaction and to assess adaptability of 26 elite bread wheat lines. A multi environment trial was conducted using 26 elite bread wheat lines along with two check cultivars of Chamran and Chamran-2 in 2014-15 and 2015-16 cropping seasons across six testing sites including; Darab (DAR), Dezful (DEZ), Ahvaz (AHV), Khorramabad (KHR), Zabol (ZAB) and Iranshahr (ISH). The sites are representative of the major irrigated wheat production agro-ecologies in southern warm and dry zone of Iran. In each year, the trials at DAR, DEZ and KHR were grown under normally irrigated conditions while trials at AHV, ZAB and ISH were grown under terminal drought stress conditions. Mixed model analysis using Restricted Maximum Likelihood (REML) method showed significant differences among spring bread wheat genotypes for grain yield in all environments. The highest and lowest BLUE means was observed at KHR15 and ZAB15, respectively. Compared to irrigated environments, genotypes showed 35.4% losses, in average, of grain yield under terminal drought stress environments. Combined analysis of variance showed that genotype × environment interaction (GEI) accounted for 9.4% of the total sum of squares. Significant GEI suggests variability in performance of bread wheat genotypes across environments. Partitioning of GEI through AMMI analysis showed that axes IPCA1, IPCA2, and IPCA3 were highly significant (P>0.01) and explained 33%, 22%, and 13% of the GE sum of squares, respectively. The polygon view of the GGE biplot grouped environments into three sectors. AMMI method and GGE biplot showed that G5 had the highest grain yield stability. G5 and G15 were generally better adapted to terminal drought stress environments (AHV14, AHV15, ISH14, ISH15, ZAB14 and ZAB15), while G28 and G8 were more adapted to irrigated environment conditions. AMMI and GGE biplot methods separated the western and southwest regions from the south and southeast test locations for identifying superior adapted spring bread wheat genotypes. Results showed that geographical location had greater impact than the effect of moisture management on the grouping of genotypes. The specific adaptation strategy is suggested for identifying adapted spring bread wheat cultivars with high grain yield and yield stability for these target environments.