Department of Biosystems Machinery Engineering, College of Agricultural and Life Science, Chungnam National University, 99 Daehak-ro, Yuseoung-gu, Daejeon, 34134, South 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.
Anal Bioanal Chem. 2018 Sep;410(22):5663-5673. doi: 10.1007/s00216-018-1189-1. Epub 2018 Jun 22.
Spectroscopic techniques for food quality analysis are limited to surface inspections and are highly affected by the superficial layers (skin or packaging material) of the food samples. The ability of spatially offset Raman spectroscopy (SORS) to obtain chemical information from below the surface of a sample makes it a promising candidate for the non-destructive analysis of the quality of packaged food. In the present study, we developed a line-scan SORS technique for obtaining the Raman spectra of packaged-food samples. This technique was used to quantify butter adulteration with margarine through two different types of packaging. Further, the significant commercial potential of the developed technique was demonstrated by its being able to discriminate between ten commercial varieties of butter and margarine whilst still in their original, unopened packaging. The results revealed that, while conventional backscattering Raman spectroscopy cannot penetrate the packaging, thus preventing its application to the quality analysis of packaged food, SORS analysis yielded excellent qualitative and quantitative analyses of butter samples. The partial least-square regression analysis predictive values for the SORS data exhibit correlation coefficient values of 0.95 and 0.92, associated with the prediction error 3.2 % and 3.9 % for cover-1 & 2, respectively. The developed system utilizes a laser line (ca. 14-cm wide) that enables the simultaneous collection of a large number of spectra from a sample. Thus, by averaging the spectra collected for a given sample, the signal-to-noise ratio of the final spectrum can be enhanced, which will then have a significant effect on the multivariate data analysis methods used for qualitative and/or qualitative analyses. This recently presented line-scan SORS technique could be applied to the development of high-throughput and real-time analysis techniques for determining the quality and authenticity various packaged agricultural products.
光谱技术在食品质量分析中的应用仅限于表面检测,并且受食品样品的表层(外皮或包装材料)影响较大。空间偏移拉曼光谱(SORS)能够从样品表面以下获取化学信息,这使得它成为一种很有前途的非破坏性分析包装食品质量的方法。在本研究中,我们开发了一种线扫描 SORS 技术,用于获取包装食品样品的拉曼光谱。该技术用于通过两种不同类型的包装定量检测黄油与人造黄油的掺假情况。此外,通过对十种商业黄油和人造黄油品种在原始未开封包装下进行区分,证明了所开发技术具有显著的商业潜力。结果表明,传统的背散射拉曼光谱无法穿透包装,因此无法应用于包装食品的质量分析,而 SORS 分析则可以对黄油样品进行出色的定性和定量分析。SORS 数据的偏最小二乘回归分析预测值的相关系数值分别为 0.95 和 0.92,相应的预测误差分别为 3.2%和 3.9%,用于覆盖物 1 和 2。所开发的系统利用一条激光线(约 14 厘米宽),能够同时从样品中收集大量光谱。因此,通过对给定样品收集的光谱进行平均,可以提高最终光谱的信噪比,这将对用于定性和/或定量分析的多元数据分析方法产生重大影响。这种新提出的线扫描 SORS 技术可应用于开发高通量和实时分析技术,以确定各种包装农产品的质量和真实性。