Genotype, environment and genotype × environment interaction effects on the performance of maize (Zea mays L.) inbred lines

Based on principal component analysis (PCA), GGE biplot analysis is an effective method to fully assess multienvironmental yield trials (METs). Additive main effects and multiplicative interaction (AMMI) is an alternative method for assessing phenotypic stability and adaptability. In this research, MET data of 14 maize inbred lines were used to perform AMMI and GGE biplot analyses. These genotypes were evaluated under diverse climatic conditions in five Iranian locations during two cropping cycles (2007 and 2008). A genotype (inbred line) by location table was used for performing the analyses. Based on both mean grain yield and yield stability, inbred lines K3615/2, K19/1, K166B and K18 proved to be superior and also had greater mean performance among the test inbred lines. Graphic analysis was used to identify the most suitable inbred lines for each test environment. Inbred lines K3615/2, K19/1, K166B, K18, K3653/2 and K3547/5 were identified as suitable in all locations. The AMMI and GGE biplot graphics revealed three separate groups of environments, i.e., three mega-environments. Group one included three sites,Karaj, Kabootar Abad and Zarghan, while group two included only Islam Abad-e-Gharb and group three onlyMiandoab. Islam Abad Gharb and Miandoab were more discriminative for genotypes. The inbred lines that were most responsive to the environment were K3615/2, K166B, K19/1 and K18; the least responsive line was K3547/5.

Genotype, environment and genotype × environment interaction effects on the performance of maize (Zea mays L.) inbred lines Keywords:

Maize , GGE biplot , AMMI , PCA , G × E interaction