Table 1.
Response Variable, Samples, and Number of Input Variables Used to Train the Different Prediction Models and the Resulting Predictive Power in Cross-Validation.
| Response Y | Freezing tolerance C24-crosses | Freezing tolerance Col-crosses | MPH in freezing tolerance |
| Samples | C24-crosses: | Col-crosses | C24-crosses: |
| 4 NA + 4 ACC | (without Col×C24): 3 NA + 3 ACC | 4 NA + 4 ACC | |
| Col×C24: | Parental lines | Col-crosses: | |
| 1 NA + 1 ACC | (without C24): | 4 NA + 4 ACC | |
| Parental lines: | 4 NA + 4 ACC | ||
| 5 NA + 5 ACC | |||
| Sample size N | 20 | 14 | 16 |
| Variables with missing values | Maltitol (MVI) | Maltitol (MVI) | Maltitol (deleted) |
| Tryptophan (MVI) | Tryptophan (deleted) | Tryptophan (deleted) | |
| Unknown 44 (MVI) | |||
| Number p of variables X | 59 | 58 | 57 |
| PP of all p variables | 0.87 | 0.82 | 0.32 |
| Optimal number j.opt of variables | 20 | 14 | 17 |
| PP of j.opt selected variables | 0.91 | 0.93 | 0.85 |
MVI, missing value imputation (column-wise mean substitution for metabolites with not more than 10% missing values). Metabolites with more than 10% missing values were deleted from the analysis. PP, predictive power (Pearson-correlation between observed response and predicted response in leave-one-out validation).