Table 4. Comparison of prediction accuracy of multi-environment GBLUP and GK model (3) with various other models published in refereed journals for the five data sets utilized in this study.

	GBLUP		GK
Wheat Data Set 1	FA	Model (3)	EB-G × E	Model (3)
E1	0.553	0.543	0.458	0.606
E2	0.611	0.720	0.644	0.713
E3	0.585	0.694	0.586	0.694
E4	0.51	0.525	0.543	0.572
	GBLUP		GK
Maize Data Set 2	EB-G × E	Model (2)	EB-G × E	Model (3)
E1	0.618	0.624	0.630	0.645
E2	0.547	0.575	0.566	0.582
E3	0.519	0.525	0.556	0.578
	GBLUP		GK
Wheat Data Set 3	GBLUP-ME	Model (3)	Model (3)
E1	0.591	0.617	0.631
E2	0.697	0.716	0.689
E3	0.505	0.512	0.551
E4	0.516	0.507	0.51
	GBLUP		GK
Wheat Data Set 4	GBLUP-ME	Model (3)	Model (3)
E1	0.513	0.601	0.616
E2	0.536	0.588	0.587
E3	0.531	0.609	0.613
E4	0.561	0.611	0.607
	GBLUP		GK
Wheat Data Set 5	GBLUP-ME		Model (3)
E1	0.575	0.583	0.637
E2	0.466	0.458	0.518
E3	0.629	0.632	0.688
E4	0.402	0.608	0.630
E5	0.376	0.596	0.597

FA (Factor Analytic) model, Burgueño et al. (2012); EB (Empirical Bayes)-G × E, Cuevas et al. (2016); GBLUP-ME, López-Cruz et al. (2015); The highest correlations in each row are in boldface. GBLUP, genomic best linear unbiased predictors: GK, Gaussian kernel.