Environmental Microbial and Food Safety Laboratory, Henry A. Wallace Beltsville Agricultural Research Centre, Agricultural Research Service, United States Department of Agriculture, 10300 Baltimore Ave., Beltsville, MD 20705, USA.
Food Chem. 2013 Jun 1;138(2-3):998-1007. doi: 10.1016/j.foodchem.2012.10.115. Epub 2012 Nov 12.
The potential of Raman chemical imaging for simultaneously detecting multiple adulterants in milk powder was investigated. Potential chemical adulterants, including ammonium sulphate, dicyandiamide, melamine, and urea, were mixed together into skim dry milk in the concentration range of 0.1-5.0% for each adulterant. Using a 785-nm laser, a Raman imaging system acquired hyperspectral images in the wavenumber range of 102-2538 cm(-1) for a 25 × 25 mm(2) area of each mixture sample, with a spatial resolution of 0.25 mm. Self-modelling mixture analysis (SMA) was used to extract pure component spectra, by which the four types of the adulterants were identified at all concentration levels based on their spectral information divergence values to the reference spectra. Raman chemical images were created using the contribution images from SMA, and their use to effectively visualise identification and spatial distribution of the multiple adulterant particles in the dry milk was demonstrated.
研究了拉曼化学成像技术同时检测奶粉中多种掺杂物的潜力。潜在的化学掺杂物，包括硫酸铵、双氰胺、三聚氰胺和尿素，以 0.1-5.0%的浓度混合在脱脂奶粉中。使用 785nm 激光，拉曼成像系统在每个混合物样品的 25×25mm(2)区域内采集了波数范围为 102-2538cm(-1)的高光谱图像，空间分辨率为 0.25mm。自建模混合分析（SMA）用于提取纯组分光谱，根据参考光谱与光谱信息发散值，在所有浓度水平下识别出了这四种掺杂物。使用 SMA 的贡献图像创建了拉曼化学图像，并展示了它们用于有效可视化干奶粉中多种掺杂物颗粒的识别和空间分布的能力。
