食品科学 ›› 2017, Vol. 38 ›› Issue (4): 290-295.doi: 10.7506/spkx1002-6630-201704047

• 安全检测 • 上一篇    下一篇

苯甲酸添加剂的拉曼高光谱分析

王晓彬,黄文倩,王庆艳,刘 宸,王超鹏,杨桂燕,赵春江   

  1. 1.沈阳农业大学信息与电气工程学院,辽宁 沈阳 110866; 2.北京农业智能装备技术研究中心,国家农业智能装备工程技术研究中心,农业部农业信息技术重点实验室, 农业智能装备技术北京市重点实验室,北京 100097
  • 出版日期:2017-02-25 发布日期:2017-02-28
  • 基金资助:
    北京市优秀人才项目(2015000021223ZK40);北京市农林科学院青年科研基金项目(QNJJ201423)

Analysis of Benzoic Acid by Raman Hyperspectral Imaging

WANG Xiaobin, HUANG Wenqian, WANG Qingyan, LIU Chen, WANG Chaopeng, YANG Guiyan, ZHAO Chunjiang   

  1. 1. College of Information and Electrical Engineering, Shenyang Agricultural University, Shenyang 110866, China; 2. Key Laboratory of Agri-informatics, Ministry of Agriculture, Beijing Key Laboratory of Intelligent Equipment Technology for Agriculture, National Research Center of Intelligent Equipment for Agriculture, Beijing Research Center of Intelligent Equipment for Agriculture, Beijing 100097, China
  • Online:2017-02-25 Published:2017-02-28

摘要: 对拉曼高光谱成像光谱仪采集苯甲酸添加剂得到的拉曼光谱信号和高光谱图像进行分析。采用小波去噪方法对原始拉曼光谱信号进行预处理,利用正交试验方法确定小波去噪参数的最优组合为小波基函数sym2、分解层数2、重调方式sln、阈值方案Rigrsure,此时信噪比为32.092。对去噪后的拉曼光谱进行谱峰归属和分析,得到了苯甲酸分子在不同波数范围内的特征振动模式,其中在1 636、1 603、1 000、793、615 cm-1和420 cm-1处的拉曼信号较强,可作为苯甲酸的拉曼特征频率。分析不同特征频率条件下的灰度图像,发现图像的亮度与特征频率的峰强相关且变化顺序具有一致性。研究结果为苯甲酸添加剂的检测分析提供研究基础。

关键词: 苯甲酸, 小波去噪, 谱峰归属, 图像分析

Abstract: Raman spectral signals and hyperspectral images of benzoic acid were collected by a Raman hyperspectral imaging spectrometer, and the information was analyzed. The original Raman signal of benzoic acid was preprocessed by a wavelet de-noising method. Optimal parameters for wavelet de-noising that provided the best signal-to-noise ratio (32.092) was determined using an orthogonal array design were established as follows: sym2 wavelet function was used, decomposition level was 2, reset mode was ‘sln’, and threshold option scheme was ‘Rigrsure’. The de-noised Raman spectra were assigned and analyzed. The characteristic vibration modes of benzoic acid in different wavenumber ranges were obtained. The strong spectral peaks at 1 636, 1 603, 1 000, 793, 615 and 420 cm-1 could be used as the Raman characteristic frequency of benzoic acid. The Raman characteristic frequencies corresponding to the gray level image obtained from the hyperspectral image were analyzed. The brightness of the image was correlated with the peak intensity of the characteristic frequency, and both changed in the same order. These research results provide a basis for the detection and analysis of benzoic acid.

Key words: benzoic acid, wavelet de-noising, spectral peak assignment, image analysis

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