From: A review of deep learning applications for genomic selection
A | Method | Yield | Protein | Oil | Moisture | Height |
---|---|---|---|---|---|---|
dualCNN | 0.452 | 0.619 | 0.668 | 0.463 | 0.615 | |
DeepGS | 0.391 | 0.506 | 0.531 | 0.31 | 0.452 | |
Dense | 0.449 | 0.603 | 0.657 | 0.427 | 0.612 | |
singleCNN | 0.463 | 0.573 | 0.627 | 0.449 | 0.565 | |
rrBLUP | 0.412 | 0.392 | 0.39 | 0.413 | 0.458 | |
BRR | 0.422 | 0.392 | 0.39 | 0.413 | 0.458 | |
Bayes A | 0.419 | 0.393 | 0.388 | 0.415 | 0.458 | |
BL | 0.419 | 0.394 | 0.388 | 0.416 | 0.458 | |
B | Interaction | Type | ASC | SE | MSE | SE |
I | BRR | 0.584 | 0.012 | 3.015 | 0.169 | |
I | NDNN | 0.626 | 0.013 | 1.891 | 0.088 | |
I | GP | 0.596 | 0.01 | 2.457 | 0.121 | |
I | PDNN | 0.627 | 0.012 | 1.912 | 0.073 | |
WI | BRR | 0.436 | 0.018 | 4.481 | 0.25 | |
WI | NDNN | 0.635 | 0.013 | 1.872 | 0.084 | |
WI | GP | 0.431 | 0.018 | 3.418 | 0.186 | |
WI | PDNN | 0.584 | 0.014 | 2.853 | 0.412 |