Table 4. Results of SRR.

Method	nR	nV	R2	$h_{\text{M}}^2$	$R_{M+QTL}^2$	$h_{M+QTL}^2$
GBLUP	75	2,000	0.053(0.008)	0.775(0.009)	0.072(0.010)	0.748(0.009)
BayesB	75	2,000	0.073(0.016)	0.768(0.009)	0.124(0.021)	0.789(0.008)
BayesC	75	2,000	0.077(0.015)	0.753(0.010)	0.123(0.021)	0.774(0.009)
GBLUP	150	2,000	0.117(0.012)	0.698(0.041)	0.157(0.013)	0.724(0.037)
BayesB	150	2,000	0.187(0.027)	0.724(0.028)	0.304(0.024)	0.799(0.018)
BayesC	150	2,000	0.190(0.026)	0.731(0.044)	0.307(0.024)	0.814(0.023)
GBLUP	500	2,000	0.266(0.011)	0.705(0.014)	0.345(0.011)	0.790(0.009)
BayesB	500	2,000	0.501(0.017)	0.672(0.010)	0.691(0.006)	0.796(0.006)
BayesC	500	2,000	0.499(0.016)	0.682(0.010)	0.691(0.007)	0.800(0.006)
GBLUP	1,000	2,000	0.409(0.009)	0.716(0.017)	0.505(0.008)	0.801(0.011)
BayesB	1,000	2,000	0.588(0.008)	0.679(0.013)	0.760(0.004)	0.803(0.007)
BayesC	1,000	2,000	0.587(0.008)	0.682(0.013)	0.761(0.004)	0.803(0.007)
GBLUP	2,000	2,000	0.528(0.011)	0.735(0.009)	0.624(0.006)	0.803(0.004)
BayesB	2,000	2,000	0.647(0.013)	0.699(0.010)	0.784(0.002)	0.803(0.002)
BayesC	2,000	2,000	0.647(0.013)	0.698(0.010)	0.784(0.002)	0.802(0.002)
GBLUP	4,000	2,000	0.609(0.007)	0.743(0.005)	0.693(0.004)	0.800(0.001)
BayesB	4,000	2,000	0.678(0.007)	0.709(0.006)	0.792(0.002)	0.801(0.001)
BayesC	4,000	2,000	0.678(0.007)	0.708(0.005)	0.792(0.002)	0.801(0.001)
GBLUP	8,000	2,000	0.673(0.005)	0.757(0.003)	0.740(0.003)	0.801(0.001)
BayesB	8,000	2,000	0.706(0.006)	0.729(0.004)	0.795(0.002)	0.801(0.001)
BayesC	8,000	2,000	0.705(0.005)	0.728(0.004)	0.795(0.002)	0.801(0.001)

SRR: markers and QTL were selected at random; n_R: number of individuals in RP; n_V: number of individuals in VP; R² and $h_{\text{M}}^2$ are the predictive ability and genomic heritability when QTL are not in the panel; $R_{M+QTL}^2$ and $h_{M+QTL}^2$ are the predictive ability and genomic heritability when QTL are in the panel