GS modela | Training population | Prediction accuracyb | |||||
---|---|---|---|---|---|---|---|
FWc | FWt | FH | PT | Brix | |||
Parametric | RR-BLUP | TGC1 | 0.822 | 0.867 | 0.821 | 0.856 | 0.670 |
TGC2 | 0.748 | 0.766 | 0.687 | 0.618 | 0.776 | ||
Combined | 0.758 | 0.802 | 0.719 | 0.765 | 0.736 | ||
BA | TGC1 | 0.824 | 0.868 | 0.821 | 0.856 | 0.673 | |
TGC2 | 0.744 | 0.761 | 0.686 | 0.624 | 0.772 | ||
Combined | 0.775 | 0.804 | 0.715 | 0.765 | 0.734 | ||
BL | TGC1 | 0.816 | 0.861 | 0.815 | 0.853 | 0.686 | |
TGC2 | 0.734 | 0.779 | 0.679 | 0.623 | 0.779 | ||
Combined | 0.766 | 0.799 | 0.708 | 0.748 | 0.739 | ||
Non-parametric | RKHS | TGC1 | 0.828 | 0.870 | 0.822 | 0.859 | 0.682 |
TGC2 | 0.758 | 0.775 | 0.700 | 0.625 | 0.784 | ||
Combined | 0.777 | 0.813 | 0.738 | 0.773 | 0.746 | ||
SVM | TGC1 | 0.804 | 0.851 | 0.797 | 0.860 | 0.690 | |
TGC2 | 0.755 | 0.772 | 0.669 | 0.594 | 0.797 | ||
Combined | 0.778 | 0.808 | 0.723 | 0.767 | 0.765 | ||
RF | TGC1 | 0.835 | 0.865 | 0.810 | 0.866 | 0.702 | |
TGC2 | 0.780 | 0.791 | 0.641 | 0.643 | 0.778 | ||
Combined | 0.812 | 0.834 | 0.728 | 0.807 | 0.751 |