Table 2.
Predictive accuracy when using all or only gene-based markers
Prediction scenario | Traita | Markers | Bayes C | RKHS | ||||||
---|---|---|---|---|---|---|---|---|---|---|
SNPS | MITE/DTX | RLX/RIX | ALL | SNPS | MITE/DTX | RLX/RIX | ALL | |||
Across | GL | Genic | 0.57 | 0.51 | 0.41 | 0.67* | 0.47 | 0.54 | 0.26 | 0.48 |
All | 0.65 | 0.42 | 0.42 | 0.66 | 0.45 | 0.50 | 0.35 | 0.48 | ||
TF | Genic | 0.71 | 0.58 | 0.50 | 0.68 | 0.71 | 0.65 | 0.69 | 0.75* | |
All | 0.71 | 0.66 | 0.56 | 0.71 | 0.68 | 0.72 | 0.67 | 0.73 | ||
Within | GL | Genic | 0.56 | 0.55 | 0.43 | 0.57 | 0.56 | 0.38 | 0.36 | 0.55 |
All | 0.61 | 0.69* | 0.43 | 0.63 | 0.59 | 0.50 | 0.45 | 0.59 | ||
TF | Genic | 0.59 | 0.55 | 0.51 | 0.62 | 0.57 | 0.61 | 0.56 | 0.57 | |
All | 0.59 | 0.63* | 0.62 | 0.60 | 0.59 | 0.65 | 0.59 | 0.60 |
*Best strategy
aGL: grain length; TF: time to flowering