Non-destructive prediction of tablet hardness by near infrared diffuse reflection spectroscopy
- Author:
Su-Jun QIU
1
Author Information
- Publication Type:Journal Article
- Keywords: Back-propagation artificial neural networks; Hardness; Near infrared diffuse reflection spectrum; PLSR
- From: Chinese Pharmaceutical Journal 2016;51(11):904-909
- CountryChina
- Language:Chinese
- Abstract: OBJECTIVE: To establish a method for predicting tablet hardness by near infrared diffuse reflection spectroscopy. METHODS: Tablet hardness value was obtained by hardness meter. Calibration model between NIR spectra and the hardness was establish by partial least squares regression (PLSR) method and BP-ANN method. RESULTS: Correlation coefficients (r), root mean squares error of cross-validation (RMSECV), and root mean square error of prediction (RMSEP) obtained by PLSR model were 0.977 8, 0.742 and 0.815 kg respectively. And the correlation coefficients of training set, monitor set and testing set by BP-ANN were 0.987 3, 0.985 6, and 0.986 8, with RSE% of 6.83%, 8.77%, and 6.69%, respectively. CONCLUSION: The prediction accuracy of BP-ANN nonlinear model is superior to the PLSR model.
