A Comprehensive Comparison Between Eberhart and Russell Joint Regression and GGE Biplot Analyses to Identify Stable and High Yielding Maize Hybrids.

Multiple environment trials (MET) are commonly conducted in plant breeding programs to evaluate cultivars/hybrids mainly to identify and recommend stable and high yielding genotypes. Although the measured yield from MET data represents the combined effects of environment (E), genotype (G) main effects and genotype-by-environment (GE) interaction effects, only G and GE are relevant to cultivar evaluation. The objective of this study was to compare the widely used Eberhart and Russell (1966) joint regression method with GGE biplot analysis to identify stable and high yielding genotypes. The study included 24 maize hybrids from advanced stage of crop pipeline. The yield data of 24 maize hybrids were obtained from 24 locations across seven Midwest states in 2007. The analysis of variance results indicated that environment (E) main effects were higher (>80%) compared to genotype (G) main effects and genotype-by-environment (GE) interaction effects together (<20%).  The Eberhart and Russell analysis identified stable hybrids (HY24> HY23 > HY22) based on the variance deviation from error mean squares estimates. However, it could not reliably identify the high yielding genotypes based on regression coefficient. On the other hand, the GGE biplot, reliably and graphically, displayed the high yielding and stable hybrids (HY07> HY20 > HY04) as well as low yielding (HY10 < HY19) genotypes consistent with their respective overall yield ranks. From the GGE biplot analysis, the genotypes suited to some specific locations/environments were also identified. On the whole, it can prospectively be stated that the GGE biplot analyses provided more comprehensive and better results compared to Eberhart and Russell joint regression analysis.