Model | HT6 | HT12 | DBH | PILO | BB | FD |
|---|
\({h}_{c}\) | 0.72 | 0.42 | 0.69 | 0.87 | 0.89 | 0.37 |
PBLUP-C | 0.38 (0.01) | 0.22 (0.01) | 0.44 (0.01) | 0.62 (0.01) | 0.61 (0.01) | 0.21 (0.01) |
GBLUP | 0.42 (0.01) | 0.24 (0.01) | 0.44 (0.01) | 0.63 (0.01) | 0.67 (0.01) | 0.23 (0.01) |
GBLUP-S | 0.35 (0.01) | 0.22 (0.01) | 0.37 (0.01) | 0.58 (0.01) | 0.72 (0.01) | 0.20 (0.01) |
GBLUP-F | 0.42 (0.01) | 0.26 (0.01) | 0.44 (0.01) | 0.63 (0.01) | 0.70 (0.00) | 0.25 (0.01) |
Accuracy | 0.58 | 0.62 | 0.64 | 0.72 | 0.81 | 0.68 |
- The prediction models showing the highest PA for a trait have their PA-estimated highlighted in italic bold. The \({h}_{c}\) is the square root of the clonal mean narrow sense heritability (\(h_{e}^{2}\)) based on PBLUP-AR model. PBLUP-C is the traditional pedigree-based best linear unbiased prediction (BLUP) including marker-based pedigree correction; GBLUP is the genomic-based BLUP; GBLUP-S is genomic-based BLUP and with marker-preselection based on the smallest p-values from genome-wide association analyses (GWAS) for each training population. In this table, the 100 smallest p-value SNPs were preselected for the budburst stage (BB) and 2000 SNPs were preselected for the other traits. GBLUP-F is a genomic-based BLUP model plus the SNP with the smallest p-value fitted as an additional fixed regression effect. This SNP was also selected based on GWAS for each training population. The accuracy for the model showing the highest PA is here roughly estimated as PA/\({h}_{c}\)
