Table III.
Principal Component Regression of MSC, SNV, and Savitzky–Golay Second Derivative-Transformed NIR Spectra for Calibration and Prediction of Letrozole and PLGA
| MSC | SNV | Savitzky–Golay | ||||
|---|---|---|---|---|---|---|
| Calibration | Prediction | Calibration | Prediction | Calibration | Prediction | |
| Samples | 36 | 36 | 36 | 36 | 36 | 36 |
| Slope | 0.957412 | 0.82900 | 0.957483 | 0.828827 | 0.977374 | 0.964158 |
| Offset | 0.448953 | 1.93057 | 0.448200 | 1.932293 | 0.238517 | 0.777366 |
| Correlation | 0.978474 | 0.96485 | 0.978511 | 0.964810 | 0.988622 | 0.990186 |
| RMSE | 1.165071 | 1.24002 | 1.164094 | 1.240839 | 0.849203 | 0.740259 |
| SEC/SEP | 1.181598 | 1.21242 | 1.180607 | 1.213250 | 0.861249 | 0.602415 |
| Bias | 1.325e-07 | 0.329 | 9.272e-08 | 0.329539 | −1.457e-07 | 0.441769 |
Second derivative transformation showed lower RMSE, SEC, SEP, and a higher correlation coefficient than MSC and SNV-treated spectra