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Raman spectroscopy method for subsurface detection of food powders through plastic layers

机译:拉曼光谱法通过塑料层对食品粉进行地下检测

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摘要

Proper chemical analyses of materials in sealed containers are important for quality control purpose. Although it is feasible to detect chemicals at top surface layer, it is relatively challenging to detect objects beneath obscuring surface. This study used spatially offset Raman spectroscopy (SORS) method to detect urea, ibuprofen and acetaminophen powders contained within one or more (up to eight) layers of gelatin capsules to demonstrate subsurface chemical detection and identification. A 785 nm point-scan Raman spectroscopy system was used to acquire spatially offset Raman spectra for an offset range of 0 to 10 mm from the surfaces of 24 encapsulated samples, using a step size of 0.1 mm to obtain 101 spectral measurements per sample. With increasing offset distance, the fraction of information from the deeper subsurface material increased compared to that from the top surface material. The series of measurements was analyzed to differentiate and identify the top surface and subsurface materials. Containing mixed contributions from the powder and capsule, the SORS of each sample was decomposed using self modeling mixture analysis (SMA) to obtain pure component spectra of each component and corresponding components were identified using spectral information divergence values. Results show that SORS technique together with SMA method has a potential for non-invasive detection of chemicals at deep subsurface layer.
机译:密封容器中材料的正确化学分析对于质量控制至关重要。尽管在上表层检测化学物质是可行的,但检测遮盖表面以下的物体相对具有挑战性。这项研究使用空间偏移拉曼光谱(SORS)方法检测一层或多层(最多八层)明胶胶囊中包含的尿素,布洛芬和对乙酰氨基酚粉,以证明地下化学物质的检测和鉴定。 785 nm点扫描拉曼光谱系统用于从24个封装样品的表面获取0到10 mm偏移范围的空间偏移拉曼光谱,步长为0.1 mm,以获得每个样品101个光谱测量值。随着偏移距离的增加,来自深层地下材料的信息所占比例与来自顶面材料的信息所占比例有所增加。分析了一系列测量值,以区分和识别顶面和地下材料。包含来自粉末和胶囊的混合成分,使用自建模混合物分析(SMA)分解每个样品的SORS,以获得每个组分的纯组分光谱,并使用光谱信息散度值识别相应的组分。结果表明,SORS技术与SMA方法一起具有对深层地下化学物质进行非侵入式检测的潜力。

著录项

  • 来源
  • 会议地点 Anaheim(US)
  • 作者单位

    Environmental Microbial and Food Safety Laboratory, Agricultural Research Service, United States Department of Agriculture, 10300 Baltimore Avenue, Building 303 BARC- East, Beltsville, MD, USA 20705;

    Environmental Microbial and Food Safety Laboratory, Agricultural Research Service, United States Department of Agriculture, 10300 Baltimore Avenue, Building 303 BARC- East, Beltsville, MD, USA 20705;

    Environmental Microbial and Food Safety Laboratory, Agricultural Research Service, United States Department of Agriculture, 10300 Baltimore Avenue, Building 303 BARC- East, Beltsville, MD, USA 20705;

    Environmental Microbial and Food Safety Laboratory, Agricultural Research Service, United States Department of Agriculture, 10300 Baltimore Avenue, Building 303 BARC- East, Beltsville, MD, USA 20705;

    Environmental Microbial and Food Safety Laboratory, Agricultural Research Service, United States Department of Agriculture, 10300 Baltimore Avenue, Building 303 BARC- East, Beltsville, MD, USA 20705;

    Environmental Microbial and Food Safety Laboratory, Agricultural Research Service, United States Department of Agriculture, 10300 Baltimore Avenue, Building 303 BARC- East, Beltsville, MD, USA 20705;

    River Hill High School, Clarksville, MD 21029;

  • 会议组织
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    spatially offset Raman spectroscopy; self modeling mixture analysis; subsurface detection; quality control;

    机译:空间偏移拉曼光谱;自建模混合物分析;地下探测;质量控制;
  • 入库时间 2022-08-26 13:45:19

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