Table 2.
Predictive accuracy based on the CV1 scheme for five traits evaluated in WW and WS trials using additive (A) and additive + dominance (AD) models [1]
| Model | Trial | GY | EPP | ASI | FFT | MFT |
|---|---|---|---|---|---|---|
| WS | ||||||
| A | WSJ10 | 0.28 (0.01) | 0.21 (0.04) | 0.69 (0.01) | 0.67 (0.01) | 0.56 (0.03) |
| WSJ11 | 0.03 (0.02) | 0.20 (0.01) | 0.43 (0.03) | 0.53 (0.01) | 0.57 (0.02) | |
| WST10 | 0.34 (0.02) | 0.61 (0.01) | 0.09 (0.03) | 0.11 (0.04) | 0.29 (0.03) | |
| WST11 | 0.17 (0.03) | 0.36 (0.03) | 0.37 (0.02) | 0.31 (0.02) | 0.33 (0.02) | |
| AD | WSJ10 | 0.36 (0.02) | 0.27 (0.03) | 0.70 (0.01) | 0.71 (0.02) | 0.63 (0.02) |
| WSJ11 | 0.49 (0.02) | 0.44 (0.02) | 0.51 (0.02) | 0.68 (0.02) | 0.64 (0.01) | |
| WST10 | 0.31 (0.02) | 0.61 (0.01) | 0.11 (0.04) | 0.09 (0.03) | 0.32 (0.03) | |
| WST11 | 0.51 (0.02) | 0.45 (0.01) | 0.40 (0.02) | 0.44 (0.02) | 0.43 (0.01) | |
| WW | ||||||
| A | WWJ10 | 0.37 (0.02) | 0.40 (0.03) | 0.52 (0.02) | 0.60 (0.01) | 0.56 (0.02) |
| WWJ11 | 0.33 (0.01) | 0.44 (0.01) | 0.61 (0.02) | 0.44 (0.01) | 0.49 (0.02) | |
| WWT10 | 0.42 (0.02) | 0.53 (0.01) | 0.54 (0.01) | 0.69 (0.01) | 0.62 (0.01) | |
| WWT11 | 0.31 (0.02) | 0.40 (0.02) | 0.50 (0.02) | 0.55 (0.02) | 0.51 (0.01) | |
| AD | WWJ10 | 0.58 (0.02) | 0.39 (0.02) | 0.52 (0.02) | 0.65 (0.02) | 0.65 (0.02) |
| WWJ11 | 0.40 (0.01) | 0.40 (0.02) | 0.60 (0.01) | 0.46 (0.02) | 0.51 (0.03) | |
| WWT10 | 0.52 (0.01) | 0.56 (0.01) | 0.54 (0.02) | 0.72 (0.01) | 0.62 (0.02) | |
| WWT11 | 0.33 (0.02) | 0.37 (0.02) | 0.48 (0.01) | 0.61 (0.01) | 0.58 (0.02) | |
Traits correspond to grain yield (GY, t/ha), number of ears per plot (EPP), anthesis-silking interval (ASI, days), female flowering time (FFT, days), and male flowering time (MFT, days)
Values within parentheses are standard deviations