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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
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
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
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
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
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
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
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
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
GRR 0.67 ± 0.056 0.42 ± 0.063 0.49 ± 0.023 0.45 ± 0.038
  1. Traits are HT: height in m; DBH: diameter at breast height in cm; VOL: stem volume in m3; VDir: acoustic velocity in km/s; WDRes: resistance to drilling; WDX-ray: wood density in kg/m3 using X-ray densitometry; MoEd: dynamic modulus of elasticity.