| Quantitative and qualitative analysis of Sildenafil Citrate tablets using NIR were developed. The mathematical models of quantitative and qualitative analysis were developed by partial least square (PLS) method and scaling to first range method, respectively. These two models were used for predicting the quantitative and qualitative analysis of unknown samples, and the recovery was100.14%(RSD=0.75%) with NIR and HPLC methods. The quantitative result between HPLC and NIR were compared. The quantitative analysis model was validated by PCA, and the optimal component of calibration set was4, and the Rl of the training set validated by cross-validation was98.91%, RMSEP was1.54. The quantitative analysis model was used to determine the samples used for validation, and the average recoveries of Amlodipine Besylate was100.14%(RSD=0.75%). The quantitative result of NIR method was compared with that of HPLC method, and there was no significant difference between these two methods. The selectivity of groups was5.09, and misjudgment rate of42samples was0%. In conclusion, this method can be applied in quantitative and qualitative analysis of sildenafil citrate tablets.Quantitative and qualitative analysis of healthy product contains sildenafil citrate using NIR were developed. Spectra of36samples were collected in liquid transmission mode. The mathematical models of quantitative and qualitative analysis was developed by principal component regression (PCA) method and scaling to first range method, respectively. These two models were used for predicting the quantitative and qualitative analysis of unknown samples, and the respectively was104.8%(RSD=6.28%) with NIR and HPLC methods. The quantitative result between HPLC and NIR were compared. The quantitative analysis model was validated by PCA, and principal component component was4, and the correlation coefficient (Rz) of the training set validated by cross-validation was99.92, RMSEP was31.5. The quantitative analysis model was used to determine the samples used for validation, and the average recoveries of Sildenafil Citrate was104.8%(RSD=6.28%). The quantitative result of NIR method was compared with that of HPLC method. There was no significant difference between these two methods’. The selectivity of between groups was4.38, and misjudgment rate of18samples was0%. In conclusion, this new method can be applied in quantitative and qualitative analysis of healty products containing sildenafil citrate.A rapid, accurate and no sample preparation required method was developed by NIR to identify41(seven categories) solid excipients widly used in pharmaceuatical industry.6batches samples in each class were collected and246raw NIR spectrograms were obtained.215NIR spectrograms were utilised to establish the calibration model and rest41spectrograms were utilised to validate the performance of the model. On the original data, second derivative9point smoothing combined with the first range of calibration was chosen as the optimum pre-processing method at3966～10414cm-1, and30solid excipients of all the41samples could be well identified by this model, namely "model1", and the other5sublibraries namely models (2～6) were developed for11excipients in order to classify every sample sufficiently. With this approach, no "error determinations" were assigned to a wrong class, which indicated the NIR method is appropriate for the identifacation of excipients in the cGMP manufacture of drug products within the pharmaceutical industry. A non-destructive and rapid quantitative analysis method:near infrared (NIR) diffuse reflectance spectroscopy was developed for identifying the species of pharmaceutical inner packing materials. Seven types of packaging materials were investigated:clear PVC, opaque PVC, PVDC, cold formed aluminium (Al)/PE, Al/Paper/PE, Aclar and Aclar/PVC2000. In this research,98samples were used to establish the model and other14ones were used to validate the model. The identity of all the samples was confirmed by infrared spectroscopy in the range of9000-4000cm-1, and the optimal qualitative model of those seven inner package materials was constructed using first derivative with9points smoothing and scaling to first range analysis. As a result, the selectivities (S) between groups were more than2, which implied all groups of different packaging materials can be uniquely identified; and the misclassified probability of unknown14samples was0%. In conclusion, the results above showed that the developed model for identification of those7package materials by NIR is reliable, and this method is simple and fast because the pretreatment for samples is not required. This method might be substitute the traditional infrared and chemical method for those materials identification.In this study, quantitative analysis of Fritillaria from seven origins and qualitative analysis of total alkaloids were developed using near infrared spectroscopy (NIR). Fritillaria delavayi Franch, Fritillaria cirrhosa D. Don, Fritillaria unibraacteate Hsiao et.K. C. Hsia, Fritillaria thunbergii Miq, Fritillaria pallidiflora Schrenk and Fritillaria ussuriensis Maxim from different origins were analysed after drying, crushing and screening. The mathematical models of quantitative and qualitative analysis were carried out by partial least square (PLS) method and scaling to first range method, respectively. These two models were used for predicting the unknown samples. The content range of total fritillaria alkaloids (according to piminine) of different Fritillariaes was from0.1%to0.25%. The optimal component of calibration set of quantitative model was8, and the correlation coefficient (R2) of the training set validated by cross-validation was99.35%, RMSECV was0.00339. The quantitative analysis models was used to determine the samples used for validation, and the average recovery of fritillaria alkaloids was97.38%(RSD=1.732%). The quantitative result of NIR method was compared with that of ultraviolet spectrum (UV) method, and there was no significant difference between these two methods. The selectivities (S) of groups were all above2, and misjudgment rate of15samples of prediction sets was0%. This method can be applied in quantitative and qualitative analysis of Fritillariaes from different origins.In this study, a NIR coupled with multivariate calibration algorithms were established for the rapid discrimination of the sea cucumber from different origins near Liaotung Peninsula, including Guanglu, Haiyang, Zhuanghe and Haxian Island. The performance of contactless fiber-coupled measurement head and fiber-coupled measurement head were compared for a better result. Finally, the spectra pre-processed by Second derivative with nine-point smoothing, and processed by the First range of scale in the ranges of8736.5～8582.2cm-1,7278.5～7147.3cm-1.6422.2～6283.3cm-1.5693.2～5484.9cm-1were selected for establishing the NIR model for discrimination of sea cucumbers. The rate of distinction was100%. Therefore, NIR provided a convenient, useful, specific technique to identify the sea cucumber from various geographical areas. This rapid method can be useful for quality control of sea cucumber production enterprise and quality supervision department, and can expand to determine the quality of other marine products. |
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