Use of non parametric statistics in estimation of genotypes stability

Abstract

The Mostly used, classical parametric approaches for an analysis of genotype x environment interaction are based on several assumptions: normality of: the distribution, homogeneity of variances, additivity. If some of mentioned assumptions are not fulfilled, the validity of these methods may be questionable. By use of nonparametric methods, which are simple and easy for analysis, all of the mentioned assumptions are avoided. in this paper we used several of non parametric techniques for analysis of genotype x environment interaction for grain yield of 24 maize (Zea mays Q hybrids through two locations in two years. Values of the stability measures shown that hybrids with the highest grain yield in the majority of cases were not the most stable. So as the value of the relative deviation in relation to the average rank classified the lowest yielding (4.9 t ha(-1)) genotype PR36B08 as the most stable genotype (S-i((3)) = 0.12). The interrelations of numerical values among methods, indicating the genotype x environment interaction obtained in this study, are different than the relation given by HUHN (1996), hence the order is as follows: van der Laan and de Kroon>KubingerHildebrand The Values of mean differences among ranks over different environments (S-i((1))) were ranged froin 2.33 to 14.83. The values of variance among ranks (Si(2)) varied from 3.33 to 154.92, while values of the relative deviations in relation to the average rank (Si 6)) ranged from 0.12 to 15.55.