基于拉曼光谱成像的食品中化学添加剂的无损检测

doi:10.7503/cjcu20160640

摘要/Abstract

摘要：

基于拉曼光谱成像技术对小麦粉中过氧化苯甲酰和L-抗坏血酸进行快速、无损、原位检测, 并对2种添加剂的空间分布进行了可视化研究. 采用实验室自行搭建的线扫描式拉曼光谱成像系统, 激发光源波长为785 nm, 有效光谱范围为0~2885.7 cm^-1. 分别在小麦粉中添加含量为0.1%~30%的过氧化苯甲酰和L-抗坏血酸, 对制备的样品进行拉曼光谱扫描, 选取感兴趣区域的光谱信号进行平均, 得到平均光谱代表该样品的拉曼信息. 分别选取过氧化苯甲酰和L-抗坏血酸的2个特征峰, 与该物质在小麦粉中的含量建立线性关系, 其决定系数R²分别为0.9828 和0.9912. 采集的特征波段拉曼图像经过自适应迭代重加权惩罚最小二乘(airPLS)方法扣除荧光背景后, 选取合适的特征峰强度作为阈值, 对校正拉曼图像进行二值化分析, 得到添加物的空间分布可视化图像. 该方法与点检测拉曼技术相比, 具有检测结果准确且检测时间较短的优势, 且可以实现不均匀样品中多种物质的同时检测与分布可视化.

关键词: 拉曼光谱成像, 小麦粉, 过氧化苯甲酰, L-抗坏血酸, 分布可视化

Abstract:

Raman chemical imaging applies the advantages of Raman spectroscopy to an imaging approach for screening large samples, allowing the presence and distribution of adulterants within a food material to be visualised. The potential of Raman chemical imaging technology for simultaneously detecting benzoyl peroxide(BPO) and L-ascorbic acid(LAA) in wheat flour powder was investigated. A line-scan Raman imaging system consists of a 785 nm laser, a fiber optic probe, a dispersive imaging spectrometer, a spectroscopic CCD camera, and a two-axis positioning table. This system acquired hyperspectral images in the effective spectral range of 0 to 2885.7 cm^-1. BPO and LAA were mixed into wheat flour powder in the concentration range of 0.1%—30% for each adulterant. The quantitative models were established to predict the content of BPO and LAA in wheat flour. The average spectrum of region of interest was used as Raman signal of the sample. The intensity of the Raman signal depends on the BPO and LAA content of wheat flour. The peak intensity of BPO at 1001, 1777 cm^-1 and LAA at 630, 1656 cm^-1 can be used for monitoring the additive levels. Linear regression models were established with the correlation coefficient(R²) of 0.9828 and 0.9912 for BPO and LAA, respectively. The adaptive iteratively reweighted Penalized Least Squares(airPLS) correction method can remove fluorescence background signals from the wheat flour powder. Single-band corrected images at unique Raman peaks identified for BPO and LAA can be used to create images for each adulterant using a simple thresholding method. The binary images of the two adulterants can be combined to create chemical images including both BPO and LAA, in which identification, spatial distribution, and morphological features of the two adulterant particles can be visualized in the background of the wheat flour powder. The high-throughput Raman chemical imaging method can be extended to authenticate other powdered foods and ingredients adulterated with Raman-active chemicals.

Key words: Raman chemical imaging, Wheat flour, Benzoyl peroxide, L-Ascorbic acid, Distributed visual

中图分类号:

O657.37

TrendMD:

翟晨, 彭彦昆, 李永玉, 赵娟. 基于拉曼光谱成像的食品中化学添加剂的无损检测. 高等学校化学学报, 2017, 38(3): 369.

ZHAI Chen, PENG Yankun, LI Yongyu, ZHAO Juan. Detection of Chemical Additives in Food Using Raman Chemical Imaging System^†. Chem. J. Chinese Universities, 2017, 38(3): 369.

图/表 7

Fig.1 Raman spectra of wheat flour(a), L-ascorbic acid(b) and benzoyl peroxide(c)

Fig.2 Raw(A) and corrected(B) Raman spectra of wheat flour with different contents of BPO

Fig.3 Prediction results for BPO(A) and LAA(B) content between the predicted values and reference values

Fig.4 Raman images(A, D), corrected Raman images(B, E) and binary images(C, F) of wheat flour with 30% content of BPO at 1001 cm-1(A—C) and 30% content of LAA at 630 cm-1(D—F)

Fig.5 Binary images of wheat flour with 10%, 1%, 0.5% and 0.1% content of BPO(A1—A4) and LAA(B1—B4), respectively

Fig.6 Raw Raman spectra of wheat flour with different contents of BPO and LAA

Fig.7 Binary images of wheat flour with 1%(A) and 0.1%(B) content of BPO and LAA

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