View Full Table | Close Full ViewTable 1.

Top nine wheat crosses based on superior progeny value (SPV) in environment 1.

 
Cross† Kinship‡ SPV20% SPV1% Mean GEBV§ SD GEBV
1×4 0.57 2.261 2.524 1.971 0.207
1×5 0.57 2.260 2.522 1.970 0.207
1×3 0.69 2.256 2.487 2.000 0.183
2×4 0.58 2.245 2.507 1.954 0.208
2×5 0.58 2.243 2.506 1.953 0.208
2×3 0.69 2.236 2.466 1.982 0.181
1×7 0.57 2.227 2.486 1.940 0.205
1×12 0.60 2.210 2.481 1.910 0.214
2×7 0.59 2.209 2.469 1.923 0.205
Line identifier equals the GEBV rank.
Fraction of shared alleles (identity by state).
§GEBV, genomic-estimated breeding value.



View Full Table | Close Full ViewTable 2.

Cross-validation accuracies () for wheat grain yield.

 
Environment 1 Environment 2
Set† RR‡ GAUSS§ RR GAUSS
1 0.49 0.61 0.37 0.37
2 0.44 0.52 0.49 0.51
3 0.41 0.44 0.48 0.49
4 0.64 0.69 0.42 0.43
5 0.34 0.51 0.31 0.31
6 0.43 0.36 0.59 0.60
7 0.64 0.71 0.54 0.55
8 0.54 0.66 0.62 0.63
9 0.57 0.62 0.42 0.44
10 0.65 0.69 0.56 0.53
Mean 0.51 0.58** 0.48 0.49
**Means significantly different at the 0.01 probability level in Environment 1.
Prediction set; the other nine sets were used for training.
RR, ridge regression.
§GAUSS, Gaussian model.



View Full Table | Close Full ViewTable 3.

Tenfold cross-validation accuracy () for maize and wheat traits.

 
Method† Wheat yield 1 Wheat yield 2 Wheat yield 3 Wheat yield 4 Maize flowering time Maize ear height Maize ear diameter
GAUSS 0.58a 0.49a 0.45a 0.54a 0.73a 0.51a 0.53ab
EXP 0.57a 0.49a 0.45a 0.54a 0.73a 0.54a 0.54a
RR 0.51b 0.48a 0.38b 0.48b 0.73a 0.51a 0.52b
BL 0.51b 0.48a 0.38b 0.47b 0.73a 0.52a 0.53ab
GAUSS, Gaussian model; EXP, exponential model; RR, ridge regression; BL, Bayesian LASSO.
Within each trait, accuracies with the same letter were not significantly different at the 0.05 probability level.