线扫描式拉曼高光谱成像技术无损检测奶粉三聚氰胺

为了实现颗粒状样本的大面积无损快速检测,该研究结合拉曼光谱和高光谱技术搭建了一套线扫描式拉曼高光谱检测系统,对奶粉和三聚氰胺颗粒混合样本进行了检测研究。研究通过高斯窗平滑法和air PLS基线校正方法分别消除了拉曼光谱中的噪声信号和荧光背景,选取三聚氰胺主要特征峰(671.71 cm-1)处的单波段图像作为是否含有三聚氰胺颗粒的判断依据。研究首先对三聚氰胺产生的拉曼信号在奶粉颗粒中的穿透深度进行了检测,随后完成了10种不同浓度的三聚氰胺奶粉混合样本的拉曼高光谱采集,对特征单波段图像中各像素点的拉曼强度平均值进行一元线性分析,并对单波段图像进行二值化处理。结果显示,在三聚氰胺特征单波段图像中,感兴趣区域内所有像素点的拉曼强度平均值与三聚氰胺浓度之间线性度较高,其决定系数R2达到了0.995 4。在二值图像中,三聚氰胺颗粒的位置信息能够直观的展现。研究结果表明,拉曼高光谱成像技术具有快速、无损和大面积检测的特点,在实际应用中具有巨大潜力。

Non-destructive detection of melamine in milk powder using Raman hyperspectral imaging technology combined with line-scanning

Abstract: As a scattering spectrum, Raman spectroscopy has some advantages in non-invasive detecting. The hyperspectral data contain not only conventional image but also spectral information in each pixel. In this study, a line-scanning Raman hyperspectral imaging system was built to detect and quantify the melamine mixed in the milk powder with large sample areas in a fast and nondestructive way. The Gaussian filter smoothing and an adaptive iteratively reweighted penalized least squares (air PLS) method were used to remove noise signal and fluorescence interference. The corrected images at 671.71 cm-1 waveband were extracted for detecting the melamine in the milk powder. Firstly, the penetration depth of Raman signal produced by melamine in the milk powder was measured. A designed two-layer sample was applied to measure the Raman signals after passing through milk layers of different thicknesses. According to the results, the optimum thickness of mixed samples was set to be 2 mm. Then, melamine-milk mixtures with 10 different concentrations were prepared for the experiment. Each mixture was collected by a designed aluminium alloy container with a sample thickness of 2 mm. In this case, the melamine particles at the bottom of mixed sample could be collected. After data preprocessing, a linear analysis of the averaged Raman intensity of each pixel was performed, and the concentration and distribution information of the melamine particles were finally obtained using a simple binarization arithmetic in the single-band image of mixtures at 671.71 cm-1 waveband. The results showed that there was a linear relationship between the melamine concentration and the average Raman intensity of all pixels in the region of interest of the corrected image at 671.71 cm-1 waveband, and the coefficient of determination was 0.9954. In the binary images, the number and spatial location information of melamine particles could be visually displayed. Meanwhile, the total number of the additive pixels increased nonlinearly. It meant that the binary images from this research represented the accumulation of multiple layers in sample. At low concentrations, the Raman signal generated from the additive particles at the sub-surface is too weak to detect. When the additive concentration increases to a certain degree, the Raman signal generated from the additive particles at the sub-surface can be collected. In these areas, the pixels are identified as additive pixels even if there is no additive particle at corresponding surface. This situation led to a significant increase in the number of additive pixels. The research demonstrates that the Raman intensity in single-band corrected images can be used for quantitative analysis of melamine, and the binary images can reveal the identification and the distribution of melamine particles in the skim milk powder. More Raman active additives in powdered food could be detected in the same way. In our research, the milk powder samples can be scanned directly without any chemical reagents. The process of converting to liquid is dispensable. The limit of detection for melamine concentration was estimated as 0.01% with a total detection area of 40 mm × 80 mm each time. The results show that the line-scanning Raman hyperspectral imaging system has shown a great potential for rapid and non-invasive measurement of samples with large areas.