BMC Genomics

Table 6 Single site GS prediction accuracies and their standard errors resulting from using the multi-sites as training population for RR-BLUP and GRR models for kNN-Fam-60% imputation method

From: Prediction accuracies for growth and wood attributes of interior spruce in space using genotyping-by-sequencing

Traits	GS model	Cross-validation
Traits	GS model	Multi-sites	PGTIS	Aleza Lake	Quesnel
HT	RR-BLUP	0.63 ± 0.001	0.37 ± 0.001	0.53 ± 0.002	0.45 ± 0.001
HT	GRR	0.62 ± 0.002	0.36 ± 0.003	0.52 ± 0.003	0.45 ± 0.002
DBH	RR-BLUP	0.77 ± 0.001	0.37 ± 0.001	0.50 ± 0.001	0.40 ± 0.001
DBH	GRR	0.77 ± 0.001	0.37 ± 0.002	0.50 ± 0.001	0.40 ± 0.001
VOL	RR-BLUP	0.73 ± 0.001	0.34 ± 0.001	0.50 ± 0.001	0.41 ± 0.001
VOL	GRR	0.72 ± 0.001	0.34 ± 0.002	0.50 ± 0.002	0.40 ± 0.002
V _Dir	RR-BLUP	0.67 ± 0.001	0.50 ± 0.001	0.47 ± 0.001	0.49 ± 0.001
V _Dir	GRR	0.66 ± 0.001	0.49 ± 0.001	0.47 ± 0.001	0.48 ± 0.002
WD _Res	RR-BLUP	0.64 ± 0.001	0.41 ± 0.001	0.48 ± 0.001	0.46 ± 0.001
WD _Res	GRR	0.64 ± 0.002	0.41 ± 0.002	0.48 ± 0.002	0.45 ± 0.003
WD _X-ray	RR-BLUP	0.62 ± 0.001	0.46 ± 0.001	0.49 ± 0.002	0.50 ± 0.001
WD _X-ray	GRR	0.62 ± 0.001	0.46 ± 0.002	0.49 ± 0.002	0.50 ± 0.002
MoE _d	RR-BLUP	0.67 ± 0.001	0.50 ± 0.001	0.46 ± 0.001	0.48 ± 0.001
MoE _d	GRR	0.66 ± 0.001	0.49 ± 0.002	0.45 ± 0.002	0.47 ± 0.002
Ave.	RR-BLUP	0.68 ± 0.055	0.42 ± 0.066	0.49 ± 0.023	0.46 ± 0.039
Ave.	GRR	0.67 ± 0.056	0.42 ± 0.063	0.49 ± 0.023	0.45 ± 0.038

Traits are HT: height in m; DBH: diameter at breast height in cm; VOL: stem volume in m³; V_Dir: acoustic velocity in km/s; WD_Res: resistance to drilling; WD_X-ray: wood density in kg/m³ using X-ray densitometry; MoE_d: dynamic modulus of elasticity.

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