Understanding the nature of genotype-by-environment (GE) interaction is an important consideration in designing strategies for its exploitation in breeding programs. Statistically, GE interactions are detected as a significant difference in the performance of genotypes across environments. Biologically, this will occur when the contribution (or levels of expression) of genes regulating a given trait differ among environments. These conditional contributions of genes are recognised by many researchers but only a few statistical methods incorporate this pattern in dissecting the phenomenon of genotype-by-environment interactions. The most prominent method so far is that described by Muir et al. (1992). Muir's method, however, is tedious to implement by manual computations. A computing program for routine analysis and evaluation of its merits with regards to reproducible results has been developed. This poster reports the results of an empirical analysis, involving diverse data sets for grain yield and protein concentration of malting barleys, which found the measure to be highly repeatable.

References

Muir, W., Nyquist, W.E. and Xu, S. (1992) Alternative partitioning of the genotype-by-environment interaction. Theoretical and Applied Genetics, 84: 193-200.

Date received: 19, 2001