SASG x ESTAB: A SAS program for computing genotype x environment stabilitystatistics

We provide a comprehensive SAS program for the computation of univariate an d multivariate stability statistics for balanced data. The program is inten ded for genotype x location x year (G x L x Y) or genotype x location (G x L) data, averaged over replications (R). It computes the symmetrical joint linear regression with the right and left solutions and Tukey's 1 df for no nadditivity, the regression coefficients (b- or beta-values), and the devia tions from regression (delta(y)) and provides the graphs of the regression lines for both genotypes and locations, Separate regression on the positive and negative sectors of the environmental indices is also conducted. The p rogram calculates Tai's alpha and lambda statistics with graphical presenta tion of the scatter of the genotypes in the alpha, lambda space. Other outp uts of the program include the univariate stability statistics Wricke's eco valence (W-i(2)), Shukla's stability variance (sigma(i)(2)), Hanson's genot ypic stability (D-i(2)), Plaisted and Peterson's theta(i), Plaisted's <(the ta)over bar>((i)), Franc's and Kannenberg's environmental variance (S-i(2)) , and coefficient of variance (S-i(2)); and the rank-based nonparametric st ability statistics S-i((2)), S-i((3)), S-i((6)), Kang's rank sum, and the s tratified rank analysis of the genotypes. The program also computes Type 4 stability, superiority measure (P-i), the desirability index of genotype pe rformance, and the pairwise genotype x environment (G x E) interaction of g enotypes with checks, It partitions the G x E interaction into that due to heterogeneity of variances and that due to imperfect correlation between th e genotype performance and performs the singular value decomposition of the G x E matrix, plotting the first two interactions' principal components.