Table 3.
Prediction accuraciesand their standard deviations (s.d.) for different WGP models
Trait |
h2 |
RR-BLUP |
LASSO |
Elastic net |
RKHS |
BayesB |
|||||
---|---|---|---|---|---|---|---|---|---|---|---|
s.d. | s.d. | s.d. | s.d. | s.d. | |||||||
Dry matter yield |
0.93 |
0.61 |
0.07 |
0.51 |
0.11 |
0.56 |
0.08 |
0.61 |
0.07 |
0.59 |
0.08 |
Plant height |
0.97 |
0.57 |
0.09 |
0.45 |
0.11 |
0.48 |
0.11 |
0.57 |
0.09 |
0.56 |
0.08 |
Lignin content |
0.88 |
0.69 |
0.07 |
0.60 |
0.08 |
0.60 |
0.10 |
0.68 |
0.07 |
0.58 |
0.09 |
Dopamine |
0.97 |
0.74 |
0.06 |
0.79 |
0.06 |
0.79 |
0.06 |
0.74 |
0.07 |
0.75 |
0.06 |
Ribitol |
0.95 |
0.49 |
0.12 |
0.61 |
0.10 |
0.63 |
0.10 |
0.50 |
0.10 |
0.50 |
0.11 |
719700-204 | 0.96 | 0.79 | 0.06 | 0.82 | 0.05 | 0.82 | 0.05 | 0.80 | 0.05 | 0.80 | 0.08 |
Results are averaged over all 100 cross-validation runs. For the agronomic traits, h2is the heritability on a line-mean basis and for the metabolites, the repeatability is shown.