Table 4 Wheat data sets
TraitEnvironmentBLBRRBayes ABayes BBIRRBAIBIR1BIR2
DTH113.0213.1812.7213.2312.8112.8512.812.66
211.8912.3710.6511.2811.6411.8811.5910.63
38.188.447.317.598.098.048.087.44
421.5922.2721.7921.6721.6121.5721.6122.7
58.869.238.488.378.788.818.788.68
814.7215.2214.5414.5814.6914.6814.6914.75
921.3821.4423.7123.9321.3621.4021.3522.22
107.728.517.277.577.677.917.627.27
116.837.126.596.746.786.746.776.77
1213.6014.4213.5613.4613.6613.6213.6013.42
GY10.070.090.070.070.070.070.070.07
20.060.080.060.060.060.060.060.06
30.060.070.060.060.060.060.060.06
40.220.240.230.230.220.220.220.23
50.390.440.260.270.400.400.400.39
60.130.150.120.130.130.130.130.13
70.400.410.430.440.400.400.400.43
  • Mean predicted mean squared error between observed and predicted values for GY and DTH of wheat lines in environments (1−11) for eight models: BL, BRR, Bayes A, Bayes B (Pérez-Rodríguez et al. 2012), BIRR, BAI, and BIR1 and BIR2. The smallest values for each trait-environment combination are in boldface. BL, Bayesian least absolute shrinkage and selection operator; BRR, RR-BLUP; BIRR, Bayesian inverse ridge regression; BAI, Bayes A inverse; BIR1, Bayesian inverse regression model 1; BIR2, Bayesian inverse regression model 2; DTH, days to heading; GY, grain yield.