Evaluation of Piecewise Direct Standardization Algorithm for Near Infrared Quantitative Model Updating
10.11895/j.issn.0253-3820.140359
- VernacularTitle:PDS算法进行近红外定量模型更新的效果评估
- Author:
Chenchen XI
;
Yanchun FENG
;
Changqin HU
- Publication Type:Journal Article
- Keywords:
Piecewise direct standardization algorithm;
Near infrared quantitative model;
Prediction results;
Error analysis
- From:
Chinese Journal of Analytical Chemistry
2014;(9):1307-1313
- CountryChina
- Language:Chinese
-
Abstract:
The near infrared ( NIR ) spectra of 76 batches of the amoxicillin capsules from different manufacturers and their corresponding content powder without capsules cell were used to find some quantitative indicators to evaluate whether the piecewise direct standardization ( PDS ) algorithm succeeded in NIR quantitative model updating. 54 batches were used to construct the NIR quantitative model for capsule preparation. All the NIR spectra of amoxicillin capsules were divided into five classes by cluster analysis, and each class can be regarded as a homology sample set. The average spectrum for each homology sample set was calculated. Ten to Fifteen spectra were selected from each homology sample set as the corresponding master spectra of the PDS algorithm to correct all the NIR spectra of the amoxicillin content powder respectively. Then the corrected spectra were predicted by the constructed NIR quantitative model for amoxicillin capsules. The prediction error for each corrected powder spectrum, and the correlation coefficient between each corrected powder spectrum and the average spectrum of the corresponding homolog sample set which the PDS master spectra came from, were calculated. Finally, the relationship between the prediction error and its corresponding correlation coefficient were studied. It was found that the correction results correlated closely with the selected master spectra set in PDS algorithm. The bigger the correlation coefficient ( r) , the better the correction results. In general, when r is less than 99%, it can be judged that the PDS correction is failed. At this condition, the prediction error is often more than 5%. Therefore, the correlation coefficient between the corrected spectrum and its corresponding average spectrum of the homology sample set can be used as an indicator to evaluate the efficiency of the PDS correction.
