Table 4. Predictive ability for Dent, using a training set size of 200 genotypes.

Model	U	SU	CD	S	R	SE
Silking, Dent, 200 genotypes
QTL	0.461	0.471	0.396	0.409	0.367	0.008
GBLUP	0.822	0.820	0.818	0.698	0.744	0.007
QGBLUP	0.842	0.829	0.822	0.696	0.729	0.008
RKHS	0.818	0.814	0.805	0.621	0.678	0.007
Tasseling, Dent, 200 genotypes
QTL	0.580	0.597	0.530	0.438	0.452	0.009
GBLUP	0.823	0.823	0.829	0.712	0.752	0.009
QGBLUP	0.839	0.832	0.826	0.707	0.741	0.009
RKHS	0.823	0.821	0.817	0.628	0.687	0.009
Yield, Dent, 200 genotypes
QTL	0.416	0.395	0.403	0.241	0.300	0.009
GBLUP	0.649	0.677	0.674	0.567	0.650	0.007
QGBLUP	0.649	0.677	0.678	0.524	0.617	0.009
RKHS	0.621	0.646	0.655	0.523	0.603	0.007

For the description of the training set construction methods U, SU, CD, S, and R see Table 1. SE indicates the mean standard error across methods.