Table 3.
The best-fitted nonlinear regression models generated on the training data set1,2
| Items, MJ/d | Nonlinear regression models | RMSE |
|---|---|---|
| ME intake | y = 76.66 × {1 − exp [−exp(−3.397) × BW0.6820]} | 4.64 |
| NE intake | y = 65.74 × {1 − exp [−exp(−3.445) × BW0.6543]} | 4.24 |
| NEm | y = 8.173 + 5.965 × 10−6 × BW3 | 1.26 |
| NEp | y = 0.6343 − 6.364 × 10−7 × BW3 + 0.2133 × NE intake − 6.239 × 10−5 × NE intake3 | 0.63 |
| NEl | y = 0.2731 − 3.976 × 10−6 × BW3 + 1.672 × 10−2 × NE intake2 | 1.50 |
1The training data for predicting ME intake, NE intake, and NEp were obtained from NE assay and ME assay, but the training data for predicting NEm and NEl were obtained only from NE assay.
2ME, metabolic energy; NE, net energy; NEm, NE for maintenance; NEp, NE retained as protein; NEl, NE retained as lipid; RMSE, root mean square error.