FTIR、ATR-FTIR和UV多光谱鉴别不同产地重楼

裴艺菲; 左智天; 赵艳丽; 张庆芝; 王元忠

doi:doi：10.3969/j.issn.1004-4957.2019.01.002

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FTIR、ATR-FTIR和UV多光谱鉴别不同产地重楼

- FTIR、ATR-FTIR和UV多光谱鉴别不同产地重楼
- Identification of Paris polyphylla Smith varyunnanensis from Different Origins Using FTIR,ATR-FTIR and UV Multispectral Data
- 分析测试学报 2019年38卷第1期页码：14-21
- 作者机构：
  
  1. 云南中医学院中药学院
  2. 云南省农业科学院药用植物研究所
- 作者简介：
- 基金信息：
  
  国家自然科学基金资助项目(81460584);云南省自然科学基金重点项目(2017FA049)
- DOI：doi：10.3969/j.issn.1004-4957.2019.01.002
  中图分类号：
- 纸质出版：2019
- 稿件说明：
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裴艺菲, 左智天, 赵艳丽, 张庆芝, 王元忠. FTIR、ATR-FTIR和UV多光谱鉴别不同产地重楼[J]. 分析测试学报, 2019,38(1):14-21.

裴艺菲, 左智天, 赵艳丽, 张庆芝, 王元忠. Identification of Paris polyphylla Smith varyunnanensis from Different Origins Using FTIR,ATR-FTIR and UV Multispectral Data[J]. 2019, 38(1): 14-21.
裴艺菲, 左智天, 赵艳丽, 张庆芝, 王元忠. FTIR、ATR-FTIR和UV多光谱鉴别不同产地重楼[J]. 分析测试学报, 2019,38(1):14-21. DOI： doi：10.3969/j.issn.1004-4957.2019.01.002.

裴艺菲, 左智天, 赵艳丽, 张庆芝, 王元忠. Identification of Paris polyphylla Smith varyunnanensis from Different Origins Using FTIR,ATR-FTIR and UV Multispectral Data[J]. 2019, 38(1): 14-21. DOI： doi：10.3969/j.issn.1004-4957.2019.01.002.

摘要

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。

Abstract

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 low level 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.

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