[Applied study on clustering of variables around latent components method in wavelength region selection with near-infrared spectroscopy].
The present paper introduced the principle of clustering of variables around latent components method, and used this method in selecting spectrum range of the NIR quantitative analysis models. Taking tobacco samples as experiment materials, we dealed with 107 sample spectra, divided the spectra into 5 clusters, and explained the information reflected by each of these 5 clusters in terms of chemistry. On this basis, we chose the corresponding wavelength range to set up the quantitative models of the total sugar, reducing sugar and nicotine by PLS method. Compared with the model based on the full NIR spectral range, Rtraining of the models based on the chosen spectral range rose from 0.977 1, 0.917 2 and 0.987 4 to 0.995 5, 0.975 1 and 0.994 4; Rtest rose from 0.977 8, 0.941 2 and 0.993 2 to 0.992 7, 0.967 9 and 0.994 0; RMSECV dropped from 1.09, 1.43, 0.14 to 1.05, 1.05 and 0.13, RMSEP dropped from 0.92, 1.17 and 0.16 to 0.39, 0.63 and 0.11 and the D value dropped from 1.274%, 1.972% and 0.829% to 0.711%, 0.843% and 0.768% for the total sugar, reducing sugar and nicotine, respectively. These data indicated that this method can improve the forecasting precision and stability of the model, so offers certain guidance on practical application.
Bao
Feng-Wei
FW
College of Chemical Engineering, Guizhou University, Guiyang 550003, China.
Peng
Qian-Rong
QR
Liu
Jing-Yan
JY
Cai
Yuan-Qing
YQ
Mao
Han-Bing
HB
Tang
Ke
K
Lü
Yan-Wen
YW