Table B1 Wheat data set 1
Env.Covariance Matrix Embedded Image (Upper Triangular) and Correlation Matrix (Lower Triangular) for uCovariance Matrix Embedded Image (Upper Triangular) and Correlation Matrix (Lower Triangular) for fVariance–Covariance Matrix Σ for ε
E1E2E3E4E1E2E3E4E1E2E3E4
GBLUP
 E10.534−0.123−0.121−0.2350.3020.074−0.0950.0630.238
 E2−0.2430.4800.3880.2550.2070.4230.3000.1590.164
 E3−0.2470.8340.4510.283−0.2560.6820.4570.1140.177
 E4−0.4830.5520.6320.4440.2360.5030.3470.2360.379
GK
 E10.728−0.159−0.224−0.2190.2000.118−0.0030.0940.154
 E2−0.2210.7140.6660.3440.4830.2990.1260.0960.149
 E3−0.2870.8600.8390.438−0.0150.4990.2130.0030.163
 E4−0.3110.4930.5790.6830.4600.3840.0140.2090.220
  • Empirical phenotypic correlation between environments: E1 vs. E2 = −0.019; E1 vs. E3 = −0.19; E1 vs. E4 = −0.12; E2 vs. E3 = 0.661; E2 vs. E4 = 0.411; E3 vs. E4 = 0.388. Variance–covariance matrix (upper triangular) and correlation matrix (lower triangular) for random effects u, f, and variance matrix for random errors ε of multi-environment model (3) including four environments (E1–E4) for linear kernel GBLUP and nonlinear Gaussian kernel (GK). Pair-wise sample phenotypic correlations between environments are given above. Env., environment; GBLUP, genomic best linear unbiased predictors: GK, Gaussian kernel.