Table 2. Prediction accuracy with QP and GWP using SE and ME models in CV1 and CV2 for traits LL and LW based on 25 NAM population.
| LL |
LW |
|||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| SE |
ME |
SE |
ME |
|||||||
| Scheme | Approach | Envi | QPa | GWPb | QPc | GWPd | QPa | GWPb | QPc | GWPd |
| CV1 | WP | E1 | 0.20 (2.2) | 0.38 (0.93) | 0.17 (2.4, −0.10) | 0.42 (1.40, 0.10) | 0.19 (2.2) | 0.40 (1.11) | 0.20 (2.6, 0.06) | 0.46 (1.29, 0.15) |
| E2 | 0.19 (2.4) | 0.41 (1.15) | 0.17 (2.4, −0.12) | 0.44 (1.60, 0.06) | 0.24 (2.4) | 0.46 (0.92) | 0.23 (2.6, −0.05) | 0.49 (1.18, 0.08) | ||
| E3 | 0.17 (2.1) | 0.38 (1.24) | 0.16 (2.4, −0.04) | 0.42 (1.57, 0.10) | 0.15 (2.0) | 0.37 (1.40) | 0.18 (2.6, 0.18) | 0.43 (1.37, 0.16) | ||
| E4 | 0.16 (2.0) | 0.37 (1.27) | 0.16 (2.4, 0.00) | 0.41 (1.64, 0.10) | 0.27 (2.7) | 0.48 (0.78) | 0.24 (2.6, −0.10) | 0.52 (1.15, 0.08) | ||
| Mean | 0.18 (2.2) | 0.39 (1.00) | 0.17 (2.4, −0.05) | 0.42 (1.47, 0.08) | 0.21 (2.3) | 0.43 (1.05) | 0.21 (2.6, 0.00) | 0.48 (1.29, 0.12) | ||
| AP | E1 | 0.27 (10.4) | 0.31 (0.15) | 0.29 (14.0, 0.09) | 0.31 (0.07, 0.00) | 0.32 (13.0) | 0.36 (0.13) | 0.34 (12.1, 0.08) | 0.37 (0.09, 0.04) | |
| E2 | 0.28 (13.1) | 0.32 (0.14) | 0.29 (14.0, 0.01) | 0.33 (0.14, 0.01) | 0.37 (12.8) | 0.42 (0.14) | 0.39 (12.1, 0.06) | 0.43 (0.10, 0.02) | ||
| E3 | 0.24 (12.8) | 0.29 (0.21) | 0.25 (14.0, 0.04) | 0.30 (0.20, 0.01) | 0.30 (10.3) | 0.34 (0.13) | 0.32 (12.1, 0.09) | 0.35 (0.09, 0.03) | ||
| E4 | 0.25 (14.0) | 0.30 (0.20) | 0.23 (14.0, −0.07) | 0.30 (0.30, 0.00) | 0.38 (12.7) | 0.42 (0.11) | 0.39 (12.1, 0.03) | 0.43 (0.10, 0.01) | ||
| Mean | 0.26 (12.6) | 0.31 (0.19) | 0.27 (14.0, 0.04) | 0.32 (0.19, 0.03) | 0.34 (12.2) | 0.39 (0.15) | 0.36 (12.1. 0.06) | 0.40 (0.11, 0.03) | ||
| CV2 | WP | E1 | 0.20 (2.1) | 0.39 (0.98) | 0.24 (1.8, 0.25) | 0.53 (1.19, 0.38) | 0.19 (2.2) | 0.41 (1.14) | 0.27 (2.0, 0.42) | 0.55 (1.05, 0.36) |
| E2 | 0.20 (2.3) | 0.41 (1.10) | 0.24 (1.8, 0.23) | 0.56 (1.30, 0.35) | 0.24 (2.5) | 0.46 (0.92) | 0.31 (2.0, 0.28) | 0.59 (0.91, 0.27) | ||
| E3 | 0.18 (2.0) | 0.38 (1.17) | 0.23 (1.8, 0.33) | 0.52 (1.24, 0.37) | 0.16 (2.0) | 0.37 (1.36) | 0.25 (2.0, 0.63) | 0.52 (1.03, 0.40) | ||
| E4 | 0.16 (2.0) | 0.38 (1.38) | 0.24 (1.8, 0.49) | 0.53 (1.23, 0.39) | 0.27 (2.7) | 0.48 (0.78) | 0.32 (2.0, 0.18) | 0.61 (0.93, 0.28) | ||
| Mean | 0.19 (2.1) | 0.39 (1.05) | 0.24 (1.8, 0.26) | 0.54 (1.30, 0.40) | 0.22 (2.4) | 0.43 (0.95) | 0.29 (2.0, 0.32) | 0.57 (0.96, 0.33) | ||
| AP | E1 | 0.27 (8.0) | 0.32 (0.19) | 0.29 (9.5, 0.09) | 0.36 (0.24, 0.12) | 0.31 (8.5) | 0.36 (0.16) | 0.35 (11.1, 0.13) | 0.40 (0.14, 0.10) | |
| E2 | 0.28 (9.8) | 0.34 (0.21) | 0.30 (9.5, 0.05) | 0.37 (0.23, 0.10) | 0.38 (10.6) | 0.43 (0.13) | 0.40 (11.1, 0.06) | 0.46 (0.15, 0.07) | ||
| E3 | 0.23 (7.8) | 0.31 (0.35) | 0.26 (9.5, 0.13) | 0.35 (0.35, 0.12) | 0.30 (7.3) | 0.35 (0.17) | 0.33 (11.1, 0.12) | 0.38 (0.15, 0.09) | ||
| E4 | 0.23 (7.4) | 0.31 (0.35) | 0.26 (9.5, 0.15) | 0.35 (0.35, 0.12) | 0.39 (11.0) | 0.43 (0.10) | 0.41 (11.1, 0.04) | 0.46 (0.12, 0.07) | ||
| Mean | 0.25 (8.3) | 0.32 (0.14) | 0.28 (9.5, 0.12) | 0.36 (0.29, 0.13) | 0.35 (9.4) | 0.39 (0.11) | 0.37 (11.1, 0.06) | 0.43 (0.16, 0.10) | ||
QP, quantitative trait loci-based prediction; GWP, genome-wide prediction; SE, single environment; ME, multienvironment; LL, leaf length; LW, leaf width; NAM, nested association mapping; Envi, environment; WP, within population; AP, across population.
a
In parentheses is the number of QTL identified by QP based on the SE model.
b
In parentheses is the gain in prediction accuracy with GWP over QP based on the SE model.
c
The first value in parentheses is the number of QTL identified by QP based on the ME model; and the second one the gain with ME over SE for QP.
d
The first value in parentheses is the gain in accuracy with GWP over QP based on the ME model; and the second one is the gain in accuracy with ME over SE using GWP.