Evaluation of phenotypic stability in canola (Brassica napus)

In order to explore the effect of genotype, environment and genotype × environment interaction (GEI) on grain yield of 15 canola genotypes in four different locations, a randomized complete block design with 3 replications in each location was laid out on 2013-2014 growing season. GGE biplot graphical method was used to visualize any relationships among treatments and environments. The results of analysis of variance showed highly significant effects among genotypes, environments (locations) and genotypes × environment interactions indicating the presence of genetic diversity and possible detection of phenotypic stability in genotypes. The first 2 principal components (PC1 and PC2) that explained 65.11 % and 19.64 % of GGE sum of squares (SS), were used to create a 2-dimensional GGE biplot. The graphics obtained from GGE biplot for clustering of the environments revealed three clusters: First group included E2 and E1, second group covered E4 and third cluster included E3. The graphics also showed the best genotype for each environment and ranked all genotypes based on all environments too. Collective analysis of the biplots suggested two canola mega-environments. The first mega-environment contained environments: E3 with genotype G10, genotype G7 gave the highest performance in environment E1, E2 and E4. Genotypes G7, G9 and G14 exhibited the highest mean yield and stability, while genotypes G1, G8 and G5 displayed the poorest mean yield and stability. On the other hand, E4 was the bes