表面增强拉曼光谱结合不同纳米基底快速检测酸性橙Ⅱ

Rapid Detection of Acid Orange Ⅱ by Surface-Enhanced Raman Spectroscopy Coated with Different Nano-Substrates

酸性橙Ⅱ作为一种偶氮类化工染料,具有致癌致畸性,因此,禁止添加于食品中。但由于酸性橙Ⅱ色泽鲜艳、着色力强、价格低廉,不法商家出于利益考虑非法添加于食品中用于着色,严重威胁到食品安全和消费者健康。酸性橙Ⅱ传统检测方法主要是利用仪器分析技术进行分析,但存在前处理复杂、耗时费力等缺点,不能满足快速检测识别的目的。表面增强拉曼光谱(SERS)技术作为一种快速、灵敏的新兴指纹光谱分析技术,在食品安全检测领域的应用受到广泛关注,因此,本文采用SERS光谱结合不同纳米材料增强基底,探索酸性橙Ⅱ的快速检测方法。首先实验室自制了金纳米颗粒溶胶,金纳米棒溶胶基底,并对其结构性能进行了表征,纳米溶胶基底尺度均匀、分散性良好。基于金纳米颗粒溶胶对两种拉曼激发光源(波长为633和780 nm)对酸性橙Ⅱ分析的影响进行了研究,结果表明基于633 nm激发光源酸性橙Ⅱ的SERS响应信号更强。在此基础上,对比了KlariteTM商业化固体基底、实验室自制金纳米颗粒溶胶和金纳米棒溶胶基底的增强性能,不同粒径金纳米颗粒溶胶对酸性橙Ⅱ的SERS分析有明显差异,粒径为(18.0±2.0) nm金纳米溶胶展现出较好的增强性能。利用增强性能差异不大的三种纳米材料基底(KlariteTM固体基底,粒径为(18.0±2.0) nm的金纳米颗粒基底,横纵比为1.8的金纳米棒基底)对系列浓度的酸性橙Ⅱ进行了SERS检测,结果表明SERS结合三种基底对酸性橙Ⅱ的最低检出浓度分别为0.2, 0.1和0.1 mg·L-1。SERS强度随着酸性橙Ⅱ浓度的增加而增强,因此探索建立了酸性橙Ⅱ的定量分析模型。研究选取1 184, 1 385和1 597 cm-1三个特征主峰,确定其不同浓度酸性橙Ⅱ所对应的特征峰强度,建立酸性橙Ⅱ标准溶液浓度与单个SERS特征峰强度之间的线性回归模型,决定系数R2的范围为0.861~0.938,RMSE为0.88~1.15 mg·L-1, RPD为2.5~4.0,其中, 1 597 cm-1特征峰强度与浓度之间的线性回归模型最佳(R2=0.933, RMSE=0.88 mg·L-1, RPD=4.0),具有良好的线性相关性。研究表明采用SERS光谱技术可对酸性橙Ⅱ进行定性定量分析,可作为一种简单、快速、高灵敏的检测方法用于色素类污染物检测。

Acid Orange Ⅱ, as an azo chemical dye, displays strong carcinogenesis and teratogenicity. Therefore, it is prohibited to use it in food industry. However, due to the bright color, good dyeing force and low price of Acid Orange Ⅱ, unscrupulous merchants illegally added Acid Orange Ⅱ to food for coloring, which seriously threatens food safety and consumer health. Acid Orange Ⅱ can be detected by traditional instrumental analysis methods. These methods have their own limitation such as complicated preprocessing, being time-consuming, and could not match the purpose of rapid detection and identification. Surface-enhanced Raman spectroscopy(SERS), as a fast, sensitive and novel fingerprint spectral analysis technology, has received extensive attention in the field of food safety detection. Therefore, this study aims to apply SERS spectroscopy technique combined with different nanosubstrates to explore the rapid detection method of Acid Orange Ⅱ. Firstly, gold nanoparticles(AuNPs), gold nanorods(AuNRs) substrate were synthesized in our laboratory, and we characterized its structure and properties using transmission electron microscipy(TEM). The results indicated that the nanosubstrates have the uniform scale and good dispersion. Then, the effect of two different Raman excitation sources was analyzed, which included the wavelengths of 633 and 780 nm. The results showed that the SERS response signal of Acid Orange Ⅱ is stronger based on the 633 nm excitation source. On this basis, three different substrates(KlariteTM commercial solid substrate, AuNPs, and AuNRs) were compared and the substrate enhancement performance was studied. The SERS signal of Acid Orange Ⅱ was significantly different based on different gold nanoparticle sizes. It exhibited better reinforcing properties for(18±2) AuNPs. Acid Orange Ⅱ standard solutions with a series of concentrations were detected using SERS combined with three nanosubstrates(KlariteTM, AuNPs with the diameter of(18±2) nm and AuNRs with an aspect ratio of 1.8), which showed almost similar enhancement for SERS signal of Acid Orange Ⅱ. The results demonstrated that the lowest detection concentrations of Acid Orange Ⅱ were 0.2, 0.1, and 0.1 mg·L-1 based on KlariteTM, AuNPs w and AuNRs substrates, respectively. As the SERS intensity increased with the increase of the concentration, the quantitative analysis models of Acid Orange Ⅱ were established. The Raman intensities of the selected peaks at 1 184, 1 385 and 1597 cm-1 were in linear relationship with the concentrations of Acid Orange Ⅱ. The linear determination coefficient R2 ranges were from 0.861 to 0.938, the RMSE is 0.88~1.15 mg·L-1, and the RPD is 2.5~4.0. The linear regression model between 1 597 cm-1 peak intensity and concentration(R2=0.933, RMSE=0.88 mg·L-1, RPD=4.0) showed the best linear correlation. The results showed SERS spectroscopy could be used for qualitative and quantitative analysis of Acid Orange Ⅱ. The proposed method, as a simple, rapid and highly sensitive approach, could be applied for detection colorants.