Application of a stability statistic to international maize yield trials

Abstract

Genotype x environment (GE) interaction encountered in experiments complicates genotype selection and varietal recommendation. The integration of yield and stability of genotypes into a single parameter may make selection and recommendation easier. Kang developed a rank-sum method that allows selection for both yield and the stability variance statistics (σ i (2) or s i (2) ) of Shukla. The objective of this research was to compare the rank-sum selection method to selection based on yield alone in five international maize (Zea mays L.) yield trials. Ranks were assigned for yield (the highest mean yield received a rank of 1) and for σ i (2) and s i (2) (the lowest value received a rank of 1). The yield and σ i (2) ranks and/or the yield and s i (2) ranks for each genotype were summed. Each trial contained two reference entries (REs). Yield rank or rank-sum of each genotype was compared to yield rank or rank-sum of the best RE (BRE). GE interaction was significant for all trials. Heterogeneity in the GE interaction due to the linear effect of a covariate (differences in fertility and/or cultural practices) was significant in Trials 1, 2, and 5. Overall, in all trials, 29 genotypes were selected on the basis of yield alone. On the basis of σ i (2) and yield rank-sum, 32 genotypes were identified, with 11 being lower yielding than the 29 yield-based selections. On the basis of s i (2) and yield rank-sum, 31 genotypes were selected, with 11 being lower yielding than the yield-bases selections. Obviously, yield is sacrificed when the rank-sum method is used in the selection process. However, selection based on yield alone may not be adequate when GE interaction is significant because of testing in diverse environments.