Soft independent modeling of class analogy (SIMCA) was successful in classifying a large library of 758 commercially available, non-blended samples of acetate, cotton, polyester, rayon, silk and wool 89% - 98% of the ...Soft independent modeling of class analogy (SIMCA) was successful in classifying a large library of 758 commercially available, non-blended samples of acetate, cotton, polyester, rayon, silk and wool 89% - 98% of the time at the 95% confidence level (p = 0.05 significance level). In the present study, cotton and silk had a 62% and 24% chance, respectively, of being classified with their own group and also with rayon. SIMCA correctly identified a counterfeit “silk” sample as polyester. When coupled with diffuse NIR reflectance spectroscopy and a large sample library, SIMCA shows considerable promise as a quick, non-destructive, multivariate method for fiber identification. A major advantage is simplicity. No sample pretreatment of any kind was required, and no adjust-ments were made for fiber origin, manufacturing process residues, topical finishes, weave pattern, or dye content. Increasing the sample library should make the models more robust and improve identification rates over those reported in this paper.展开更多
AIM: A near-infrared diffuse reflectance analysis (NIRDRA) method was developed for rapid non-destructive quantitative determination of clarithromycin in capsule. METHOD:All spectra were measured with a near-infrared ...AIM: A near-infrared diffuse reflectance analysis (NIRDRA) method was developed for rapid non-destructive quantitative determination of clarithromycin in capsule. METHOD:All spectra were measured with a near-infrared spectrometer equipped with a PbS detector, an external integrating sphere and a rotating sample cup. Each sample was put into the sample cup and was scanned from 12*#000 cm -1 to 4*#000 cm -1 , and each sample spectrum was obtained as an automatic mean of 64 scans. No spectrum pre-processing method was used, and a spectral region, 7*#502 ～5*#446 cm -1 , was selected to develop a mathematical model by partial least square method. RESULT: The optimal rank and mean square error determined by cross validation method was 7 and 0.00306, respectively. The average recovery and RSD of clarithromycin was 100% and 1.33%, respectively. CONCLUSION: Results showed that the NIRDRA method was rapid, simple, nondestructive and sensitive. It can be applied to predict the content of clarithromycin in capsule.展开更多
文摘Soft independent modeling of class analogy (SIMCA) was successful in classifying a large library of 758 commercially available, non-blended samples of acetate, cotton, polyester, rayon, silk and wool 89% - 98% of the time at the 95% confidence level (p = 0.05 significance level). In the present study, cotton and silk had a 62% and 24% chance, respectively, of being classified with their own group and also with rayon. SIMCA correctly identified a counterfeit “silk” sample as polyester. When coupled with diffuse NIR reflectance spectroscopy and a large sample library, SIMCA shows considerable promise as a quick, non-destructive, multivariate method for fiber identification. A major advantage is simplicity. No sample pretreatment of any kind was required, and no adjust-ments were made for fiber origin, manufacturing process residues, topical finishes, weave pattern, or dye content. Increasing the sample library should make the models more robust and improve identification rates over those reported in this paper.
文摘AIM: A near-infrared diffuse reflectance analysis (NIRDRA) method was developed for rapid non-destructive quantitative determination of clarithromycin in capsule. METHOD:All spectra were measured with a near-infrared spectrometer equipped with a PbS detector, an external integrating sphere and a rotating sample cup. Each sample was put into the sample cup and was scanned from 12*#000 cm -1 to 4*#000 cm -1 , and each sample spectrum was obtained as an automatic mean of 64 scans. No spectrum pre-processing method was used, and a spectral region, 7*#502 ～5*#446 cm -1 , was selected to develop a mathematical model by partial least square method. RESULT: The optimal rank and mean square error determined by cross validation method was 7 and 0.00306, respectively. The average recovery and RSD of clarithromycin was 100% and 1.33%, respectively. CONCLUSION: Results showed that the NIRDRA method was rapid, simple, nondestructive and sensitive. It can be applied to predict the content of clarithromycin in capsule.
