School of Food and Biological Engineering, Engineering Research Center of Bio-process, Ministry of Education , Hefei University of Technology , Hefei , Anhui 230009 , China.
State Key Laboratory of High Performance Ceramics and Superfine Microstructure , Shanghai , 200050 , China.
ACS Sens. 2019 Jul 26;4(7):1798-1805. doi: 10.1021/acssensors.9b00354. Epub 2019 Jun 28.
The quality and safety of edible oils is a momentous but formidable challenge, especially regarding identification of oil type, oxidation, and adulteration. Most conventional analytical methods have bottlenecks in sensitivity, specificity, accessibility, or reliability. Surface-enhanced Raman spectroscopy (SERS) is promising as an unlabeled and ultrasensitive technique but limited by modification of inducers or surfactants on metal surfaces for oil analysis. Here, we develop a quantitative SERS analyzer on two-liquid interfacial plasmonic arrays for direct quality classification of edible oils by a portable Raman device. The interfacial plasmonic array is self-assembled through mixing the gold nanoparticle (GNP) sols and oil sample dissolved in chloroform without any surfactants or pretreatments. Different kinds of edible oils dissolved in chloroform directly participate in self-assembly of plasmonic arrays that finally localizes onto a three-dimensional (3D) oil/water interface. The 3D plasmonic array is self-healing, shape adaptive, and can be transferred to any glass containers as a substrate-free SERS analyzer for direct Raman measurements. It produces sensitive responses of SERS on different kinds of edible oils. By virtue of principal component analysis (PCA), this analyzer is able to quickly distinguish six edible oils, oxidized oils, and adulterated oils. Moreover, the solvent chloroform generates unique and stable SERS bands that can utilized as an inherent internal standard (IIS) to calibrate SERS fluctuation and greatly improve quantitation accuracy. Compared to conventional lab methods, this analyzer avoids complex and time-consuming preprocessing and provides significant advantages in cost, speed, and utility. Our study illuminates a facile way to determine edible oil quality and promises great potential in food quality and safety analysis.
食用油的质量和安全是一个重大而艰巨的挑战，特别是在识别油的类型、氧化和掺假方面。大多数传统的分析方法在灵敏度、特异性、可及性或可靠性方面存在瓶颈。表面增强拉曼光谱（SERS）作为一种非标记和超灵敏的技术具有很大的应用前景，但受到金属表面上诱导剂或表面活性剂的修饰限制，因此不适合用于油分析。在这里，我们开发了一种基于双液相等离子体阵列的定量 SERS 分析仪，通过便携式拉曼设备对食用油进行直接质量分类。该等离子体阵列通过混合金纳米粒子（GNP）溶胶和氯仿中溶解的油样而自组装，无需使用任何表面活性剂或预处理。不同种类的食用油直接溶解在氯仿中参与等离子体阵列的自组装，最终定位于三维（3D）油水界面上。3D 等离子体阵列具有自修复、形状自适应的特点，可以转移到任何玻璃容器上作为无基底的 SERS 分析仪，用于直接拉曼测量。它对不同种类的食用油产生敏感的 SERS 响应。通过主成分分析（PCA），该分析仪能够快速区分六种食用油、氧化油和掺假油。此外，溶剂氯仿产生独特且稳定的 SERS 带，可作为固有内标（IIS）用于校准 SERS 波动，极大地提高定量准确性。与传统的实验室方法相比，该分析仪避免了复杂和耗时的预处理，并在成本、速度和实用性方面具有显著优势。我们的研究阐明了一种确定食用油质量的简单方法，并有望在食品质量和安全分析方面具有巨大的潜力。
