|
r
| Â | Â | GSA/PS efficiency ratioe | Â | GSB/PS efficiency ratioe |
---|
Traita | Phenotypic data | GS-modelled datab |
H
c
| GSA rAcd | tP = 1 | tP = 2 | GSB rAcf | tP = 1 | tP = 2 |
---|
GY | 0.377 | 0.402 | 0.632 | 0.390 | 1.801 | 3.602 | 0.262 | 1.209 | 2.418 |
OF | 0.837 | 0.827 | 0.929 | 0.690 | 2.170 | 4.340 | 0.445 | 1.398 | 2.796 |
LS | 0.398 | 0.436 | 0.609 | 0.485 | 2.323 | 4.647 | 0.420 | 2.014 | 4.029 |
SW | 0.831 | 0.836 | 0.932 | 0.723 | 2.266 | 4.531 | 0.327 | 1.024 | 2.049 |
- a GY, grain yield; OF, onset of flowering; LS, lodging susceptibility; SW, individual seed weight
- b Using Bayesian Lasso modelling trained on all genotype data
- c Assuming experiments with three replicates (as the current phenotyping experiments)
- d Using Bayesian Lasso modelling for prediction of independent lines, using 50 repetitions of 10-fold stratified cross-validation per individual analysis
- e As ratio (iG rAc / tG) / (iP H / tP), where iG and iP are standardized selection differentials for GS and PS, respectively, setting iG = 1.46 iP to approach same evaluation costs; and tG and tP are cycle duration for GS and PS, setting tG = 0.5 and tP = 1 (two test sites in the same test year) or tP = 2 (two test years in the same site)
- f Using Bayesian Lasso model training on data of one RIL population for prediction within each of two other populations