Explaining genotype by environment (GE) interaction is important in breeding programs because environmental effects are very often greater than genotypic effects in multi-environment trials. Statistical methods that select for high yield and stability have been proposed, but have not been compared for their usefulness especially for nonparametric methods. We compared fourteen nonparametric methods used for analyzing GE interaction at a set of experimental lentil data (11 genotypes at 20 environments). Nonparametric methods consist of six Huehn’s statistics (S1, S2, S3, S4, S5 and S6), four Thennarasu’s statistics (NP1, NP2, NP3 and NP4), tow Sabaghnia’s statistics (NS1 and NS2), Kang’s RS and nonparametric method of Fox et al. (1990). Considering mean yield versus nonparametric stability values via their plotting in a plot, indicated four different sections as A, B, C and D. The genotype fall in the section D were the most favorable genotypes due to high mean yield as well as high stability performance. Plot of the most nonparametric methods showed that genotypes G1 (1.21 t ha-1), G2 (1.34 t ha-1) and G5 (1.38 t ha-1) were the most favorable genotypes and so these genotypes considered both yield and stability simultaneously. Although, most of the nonparametric methods have static (biological) concept of stability and measure the real concept of stability but plotting them versus mean yield and selecting the genotypes of section D, could identify relatively the high mean yield genotypes as the most stable ones.
