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According to literature, a detailed paper has not been published yet on using   non-parametric stability statistics for evaluating genotypic stability in   protein content (PC) of wheat. Thus, this study aimed to investigate the   stability for PC of wheat using sixteen non-parametric stability measures   (YSD-PC standard deviation, RM-Rank mean, RSD-Rank’s standard deviation,   RS-Rank Sum stability statistic, PA-Percentage of adaptability, R1 and   R2-Range indexes, TOP-Ranking, Si(1), Si(2), Si(3), Si(6), NPi(1), NPi(2)   NPi(3)and NPi(4) rank statistics, together with Y-PC mean). The study   included 13 wheat genotypes, consisting of 5 registered cultivars and 8   breeding lines, selected from National Wheat Breeding Program of Turkey. The   genotypes were grown in ten rain-fed environments, representative of major   rain-fed wheat-growing areas of Turkey, during 2011-2013 cropping seasons.   The ANOVA showed that the effects due to environments (E), genotypes (G) and   GE interaction (GEI) were significant (P < 0.01). Spearman’s rank correlation   and principal component analyses (PCA) also revealed that two types of   associations were found between the stability parameters: the first type   included Si(1), Si(2), Si(3), Si(6), NPi(1), NPi(2) NPi(3), NPi(4), RSD and   YSD parameters which were related to static stability, whereas the second   type consisted of the Y, RM, TOP, PA, RS, R1 and R2 parameters which are   related to dynamic concept of stability. Among the 8 breeding lines, G7 and   G8 were the best genotypes in terms of both high PC and stability. In   conclusion it could be suggested that dynamic non-parametric stability   statistics should be used for selecting genotypes with high PC and stable   when tested across a wide range of environments

Non-parametric stability analyses of protein content in multi-environment trials of wheat (T. aestivum L.)