β_{et} (%)(H_{2}|H_{1}) | β_{ft} (%)(H_{1}|H_{0}) | |||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
L(cM) | α%→5 | 1 | 0.1 | 5 | 1 | 0.1 | n_{p} | df_{e} | df_{f} | AIC | ||
S _{1} | MA | 66.0 ± 2.03 | 67 | 41 | 16 | 67 | 45 | 22 | 8 | 3 | 5 | 10.8 |
MG | 65.4 ± 2.56 | 57 | 29 | 6 | 64 | 34 | 8 | 21 | 9 | 11 | ||
S _{2} | MA | 61.7 ± 0.89 | 97 | 87 | 70 | 94 | 87 | 67 | 8 | 3 | 5 | 12.4 |
MG | 62.5 ± 1.45 | 88 | 71 | 47 | 91 | 78 | 49 | 21 | 9 | 11 | ||
S _{3} | MA | 59.8 ± 0.49 | 100 | 99 | 94 | 100 | 99 | 97 | 8 | 3 | 5 | 12.2 |
MG | 61.1 ± 0.68 | 100 | 95 | 81 | 100 | 98 | 90 | 21 | 9 | 11 |
The results of 200 Monte-Carlo runs are presented for single-QTL situations (see Table 1). L is the estimated QTL location (the simulated value of L is 60 cM); α is significance level; n_{p} is the number of parameters specifying the model. To reduce n_{p}, the vector of mean values across environments was calculated before starting the optimization procedure for the tests 3, 3a, and 3b (for either MA or MG); df_{f} and df_{e} are the degrees of freedom for the tests of QTL presence (H_{1} vs. H_{0}) and QTL × E interaction (H_{2} vs. H_{1}), respectively.