| Trait | |||||||
---|---|---|---|---|---|---|---|---|
AGW | ADG | BJS | FCR | LMA | LMD | BF | TN | |
SNP accuracy for predicting phenotypic values \({\hat{\text{R}}}_{{0}_{\text{jp}}}=\text{corr}({\hat{\text{g}}}_{{0}_{\text{j}}},{\text{y}}_{0})\) | ||||||||
 A-only, Model-6 | 0.251 | 0.258 | 0.258 | 0.197 | 0.402 | 0.363 | 0.387 | 0.401 |
 A + D, Model-5 | 0.252 | 0.259 | 0.244 | 0.202 | 0.401 | 0.364 | 0.387 | 0.405 |
 A + D over A (%) | 0.381 | 0.328 | − 5.588 | 2.624 | − 0.123 | 0.496 | 0.174 | 0.856 |
Best SNP prediction model (the SNP model in italic font, A-only or A + D) | ||||||||
 \({ \hat{\text{R}}}_{{0}_{\text{jp}}}=\text{corr}({\hat{\text{g}}}_{{0}_{\text{j}}},{\text{y}}_{0})\) | 0.252 ± 0.032 | 0.259 ± 0.028 | 0.258 ± 0.033 | 0.202 ± 0.052 | 0.402 ± 0.042 | 0.364 ± 0.055 | 0.387 ± 0.061 | 0.405 ± 0.055 |
 \({\text{ R}}_{{0}_{\text{jp}}}={\text{R}}_{{0}_{\text{j}}}\sqrt{{\text{h}}_{\text{j}}^{2}}\) | 0.285 ± 0.010 | 0.290 ± 0.009 | 0.156 ± 0.013 | 0.241 ± 0.012 | 0.432 ± 0.008 | 0.418 ± 0.010 | 0.407 ± 0.015 | 0.405 ± 0.010 |
 \({\text{ R}}_{{0}_{\text{j}}}=\text{corr}({\hat{\text{g}}}_{{0}_{\text{j}}},{\text{g}}_{{0}_{\text{j}}})\) | 0.613 ± 0.010 | 0.624 ± 0.01 | 0.559 ± 0.016 | 0.579 ± 0.015 | 0.757 ± 0.004 | 0.722 ± 0.009 | 0.718 ± 0.010 | 0.707 ± 0.007 |
Haplotype prediction accuracy | ||||||||
 Best model | H | H | H | D + H | H | A + D + H | A + D + H | A + D + H |
 Best blocking | 500 kb | 500 kb | 100 kb | 1 Mb | Genes | Genes | 1 Mb | Genes |
 \({ \hat{\text{R}}}_{{0}_{\text{jp}}}=\text{corr}({\hat{\text{g}}}_{{0}_{\text{j}}},{\text{y}}_{0})\) | 0.270 ± 0.029 | 0.276 ± 0.027 | 0.277 ± 0.026 | 0.212 ± 0.066 | 0.413 ± 0.043 | 0.371 ± 0.055 | 0.392 ± 0.062 | 0.406 ± 0.053 |
 Accuracy increase (%) | 7.14 | 6.56 | 7.36 | 4.95 | 2.74 | 1.92 | 1.29 | 0.25 |
 \({\text{ R}}_{{0}_{\text{jp}}}={\text{R}}_{{0}_{\text{j}}}\sqrt{{\text{h}}_{\text{j}}^{2}}\) | 0.292 ± 0.006 | 0.298 ± 0.005 | 0.178 ± 0.011 | 0.248 ± 0.014 | 0.431 ± 0.006 | 0.417 ± 0.010 | 0.413 ± 0.015 | 0.401 ± 0.010 |
 \({\text{ R}}_{{0}_{\text{j}}}=\text{corr}({\hat{\text{g}}}_{{0}_{\text{j}}},{\text{g}}_{{0}_{\text{j}}})\) | 0.647 ± 0.005 | 0.650 ± 0.004 | 0.572 ± 0.012 | 0.549 ± 0.012 | 0.743 ± 0.004 | 0.710 ± 0.008 | 0.693 ± 0.009 | 0.695 ± 0.007 |