Research Article
A Dataset on Corn Silage in China Used to Establish a Prediction Model Showing Variation in Nutrient Composition
Table 7
Comparison of performance of PLSR and the BP-ANN algorithm for predicting nutrient contents of whole plant corn silage.
| Nutrition index | Model | Calibration set | Prediction set | R2c | RMSEC | R2p | RMSEP |
| DM | PLSR | 0.836 | 0.675 | 0.823 | 0.701 | BP-ANN | 0.900 | 0.550 | 0.845 | 0.642 |
| CP | PLSR | 0.903 | 0.407 | 0.900 | 0.418 | BP-ANN | 0.945 | 0.293 | 0.927 | 0.519 |
| EE | PLSR | 0.788 | 0.261 | 0.763 | 0.276 | BP-ANN | 0.886 | 0.420 | 0.853 | 0.579 |
| Ash | PLSR | 0.795 | 0.543 | 0.779 | 0.564 | BP-ANN | 0.902 | 0.806 | 0.847 | 0.792 |
| NDF | PLSR | 0.921 | 1.756 | 0.916 | 1.813 | BP-ANN | 0.965 | 0.650 | 0.935 | 0.627 |
| ADF | PLSR | 0.910 | 1.281 | 0.904 | 1.321 | BP-ANN | 0.991 | 0.667 | 0.975 | 0.993 |
| Starch | PLSR | 0.933 | 1.952 | 0.929 | 2.004 | BP-ANN | 0.972 | 0.763 | 0.944 | 0.761 |
| Ca | PLSR | 0.418 | 0.061 | 0.376 | 0.064 | BP-ANN | 0.730 | 0.806 | 0.509 | 0.792 |
| | PLSR | 0.499 | 0.029 | 0.477 | 0.030 | BP-ANN | 0.615 | 0.806 | 0.453 | 0.792 |
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