引用本文:
Dong Wang, Yun Sheng Ding, Jin Li Cao, Yue He, Sheng Feng Ye, Shun Geng Min. Study of spatial distribution for the active ingredient in ibuprofen tablet based on near-infrared micro-imaging technology[J]. Chinese Chemical Letters,
2011, 22(11): 1335-1338.
doi:
10.1016/j.cclet.2011.07.001
Citation: Dong Wang, Yun Sheng Ding, Jin Li Cao, Yue He, Sheng Feng Ye, Shun Geng Min. Study of spatial distribution for the active ingredient in ibuprofen tablet based on near-infrared micro-imaging technology[J]. Chinese Chemical Letters, 2011, 22(11): 1335-1338. doi: 10.1016/j.cclet.2011.07.001
Citation: Dong Wang, Yun Sheng Ding, Jin Li Cao, Yue He, Sheng Feng Ye, Shun Geng Min. Study of spatial distribution for the active ingredient in ibuprofen tablet based on near-infrared micro-imaging technology[J]. Chinese Chemical Letters, 2011, 22(11): 1335-1338. doi: 10.1016/j.cclet.2011.07.001
Study of spatial distribution for the active ingredient in ibuprofen tablet based on near-infrared micro-imaging technology
摘要:
The NIR micro-images of ibuprofen tablets were collected in this research. Compare correlation imaging and principal component analysis (PCA) with histogram were applied to acquire the spatial distribution of ibuprofen granule. The result indicated that a similar distribution trend can be acquired by both of the two methods mentioned above; the information of PC2 results from ibuprofen mainly since the correlation coefficient between PC2 loading vector and the NIR spectrum of ibuprofen is 0.9930. The result of PCA indicated that the information of PC2 results from ibuprofen mainly for both the low and the high content of ibuprofen in the tablets. The correlation coefficient between the data of the two PC2 loading vectors of the low and the high content of ibuprofen in the tablets is 0.9998, which indicates that the result of PCA is stable and reliable.
English
Study of spatial distribution for the active ingredient in ibuprofen tablet based on near-infrared micro-imaging technology
Abstract:
The NIR micro-images of ibuprofen tablets were collected in this research. Compare correlation imaging and principal component analysis (PCA) with histogram were applied to acquire the spatial distribution of ibuprofen granule. The result indicated that a similar distribution trend can be acquired by both of the two methods mentioned above; the information of PC2 results from ibuprofen mainly since the correlation coefficient between PC2 loading vector and the NIR spectrum of ibuprofen is 0.9930. The result of PCA indicated that the information of PC2 results from ibuprofen mainly for both the low and the high content of ibuprofen in the tablets. The correlation coefficient between the data of the two PC2 loading vectors of the low and the high content of ibuprofen in the tablets is 0.9998, which indicates that the result of PCA is stable and reliable.
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