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利用反射镜提高薄层和粉末食品分析中拉曼成像的灵敏度。

Improving Sensitivity in Raman Imaging for Thin Layered and Powdered Food Analysis Utilizing a Reflection Mirror.

机构信息

Department of Biosystems Machinery Engineering, College of Agricultural and Life Science, Chungnam National University, 99 Daehak-ro, Yuseong-gu, Daejeon 34134, Korea.

Environmental Microbial and Food Safety Laboratory, Agricultural Research Service, U.S. Department of Agriculture, Powder Mill Rd. Bldg. 303 BARC East, Beltsville, MD 20705, USA.

出版信息

Sensors (Basel). 2019 Jun 15;19(12):2698. doi: 10.3390/s19122698.

Abstract

Raman imaging has been proven to be a powerful analytical technique for the characterization and visualization of chemical components in a range of products, particularly in the food and pharmaceutical industries. The conventional backscattering Raman imaging technique for the spatial analysis of a deep layer suffers from the presence of intense fluorescent and Raman signals originating from the surface layer which mask the weaker subsurface signals. Here, we demonstrated the application of a new reflection amplifying method using a background mirror as a sample holder to increase the Raman signals from a deep layer. The approach is conceptually demonstrated on enhancing the Raman signals from the subsurface layer. Results show that when bilayer samples are scanned on a reflection mirror, the average signals increase 1.62 times for the intense band at 476 cm of starch powder, and average increases of 2.04 times (for the band at 672 cm) for a subsurface layer of high Raman sensitive melamine powder under a 1 mm thick teflon sheet. The method was then applied successfully to detect noninvasively the presence of small polystyrene pieces buried under a 2 mm thick layer of food powder (a case of powdered food adulteration) which otherwise are inaccessible to conventional backscattering Raman imaging. In addition, the increase in the Raman signal to noise ratio when measuring samples on a mirror is an important feature in many applications where high-throughput imaging is of interest. This concept is also applicable in an analogous manner to other disciplines, such as pharmaceutical where the Raman signals from deeper zones are typically, substantially diluted due to the interference from the surface layer.

摘要

拉曼成像是一种强大的分析技术,可用于对多种产品(尤其是食品和制药行业)中的化学物质进行定性和可视化分析。传统的背散射拉曼成像技术在对深层进行空间分析时,受到来自表面层的强烈荧光和拉曼信号的影响,这些信号会掩盖较弱的次表层信号。在这里,我们展示了一种新的反射增强方法的应用,该方法使用背景反射镜作为样品架来增强深层的拉曼信号。该方法通过增强次表层的拉曼信号来进行概念验证。结果表明,当双层样品在反射镜上扫描时,对于淀粉粉末的 476cm 处的强带,平均信号增强了 1.62 倍;对于在 1mm 厚聚四氟乙烯片下的高拉曼敏度三聚氰胺粉末的次表层,平均信号增强了 2.04 倍(对于 672cm 处的带)。该方法随后成功地用于非侵入性检测埋在 2mm 厚食品粉末层下的小聚苯乙烯颗粒(食品掺假的情况),而传统的背散射拉曼成像技术则无法检测到这些颗粒。此外,当在反射镜上测量样品时,拉曼信号的信噪比提高是许多高吞吐量成像感兴趣的应用中的一个重要特征。该概念在其他领域也具有类似的适用性,例如在制药领域,由于来自表面层的干扰,来自更深层的拉曼信号通常会被大幅稀释。

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