FTIR、ATR-FTIR和UV多光谱鉴别不同产地重楼

测定了云南省及贵州省6个不同产地重楼的FTIR、ATR-FTIR及UV信息,并对ATR-FTIR光谱数据进行ATR校正(ATR-FTIR-A)、一阶导数(FD)、二阶导数(SD)、标准正态变量(SNV)等预处理,结合偏最小二乘判别分析(PLS-DA)与支持向量机(SVM)建立了单光谱与低级数据融合分类判别模型。结果表明,校正后的重楼ATR-FTIR(ATR-FTIR-A)光谱信息与KBr压片法展现的信息基本吻合; UV二阶导数图谱较原始图谱分辨率提高; ATR-FTIR-A单光谱及ATR-FTIR-A-UV低级数据融合的PLS-DA及SVM模型鉴别效果最好,预测正确率均达到100. 00%。基于ATR-FTIR-A建立的PLS-DA或SVM产地鉴别模型分类正确率高,在实际生产应用中有简便、高效、准确等优点,若采用ATR-FTIR-A-UV建立模型可进一步加强模型稳定性。

Identification of Paris polyphylla Smith var. yunnanensis from Different Origins Using FTIR,ATR-FTIR and UV Multispectral Data

In this paper,Fourier transform infrared spectroscopy(FTIR),attenuated total reflection Fourier transform infrared spectroscopy( ATR-FTIR) and ultraviolet( UV) spectra of the samples from six different areas in Yunnan and Guizhou provinces were collected,and the ATR-FTIR data were processed by ATR calibration. The models for single spectra and low-level data fusion were established using different pretreatments including first derivatives( FD),second derivatives( SD) and standard normal variables( SNV) combined with partial least squares discriminant analysis( PLS-DA) and support vector machine( SVM). Results showed that the corrected ATR-FTIR( ATR-FTIR-A) spectral information was in agreement with the FTIR spectra. Additionally,second derivative processing could improve the UV resolution. ATR-FTIR-A and ATR-FTIR-A-UV lowlevel data fusion models had the highest accurate rate( 100. 00%) and the best parameter values,which were established to identify P. polyphylla from different regions by PLS-DA and SVM,respectively. Therefore,ATR-FTIR-A,with the simple and nondestructive characteristic in sample pretreatment,had a better performance than FTIR in identification of P. polyphylla of different geographical origins. It was accurate in practical production and application. However,ATR-FTIR-A-UV had a better performance than PLS-DA or SVM with only one kind of spectra.