Table 3.

Accuracy ¹ of prediction of seven linear methods in seven training scenarios for line B2

	Training dataset
Model	B1	B2	W1	B1 + B2	B1 + W1	B2 + W1	B1 + B2 + W1
BLUP2	-	0.220	-	-	-	-	-
GBLUP_VR	0.123	0.301	0.123	0.303	0.173	0.332	0.343
GBLUP_%id	0.147	0.329	0.136	0.336	0.198	0.352	0.376
RRBLUP	0.129	0.359	0.142	0.373	0.176	0.369	0.390
RRPCA	0.143	0.448	0.109	0.476	0.185	0.463	0.494
BSSVS	0.118	0.316	0.112	0.327	0.150	0.346	0.356
BayesC	0.111	0.338	0.106	0.318	0.139	0.354	0.357

BLUP: conventional BLUP using a pedigree based relationship matrix; G-BLUP: Genome-enabled Best Linear Unbiased Prediction (G-BLUP); RRBLUP: Ridge Regression BLUP; RRPCA: Ridge Regression with PCA reduction; BayesSSVS: Bayesian Stochastic Search Variable Selection; BayesC; ¹approximated SE of the accuracies of the genomic prediction models ranged from 0.097-0.102; ²for BLUP, only the analysis including the line itself was performed, because there are no pedigree relations between lines.