Rapid and sensitive surface‐enhanced Raman spectroscopy (SERS) method combined with gold nanoparticles for determination of paraquat in apple juice

Abstract

This work showed that SERS combined with gold nanoparticles could determine paraquat in apple juice. As a simple, rapid and ultrasensitive method, it has great practical potential for detection of other contaminants in a variety of foods. © 2018 Society of Chemical Industry.

Rapid and sensitive detection of pesticide residues using dynamic surface‐enhanced Raman spectroscopy

“…The SERS spectral features of paraquat, thiabendazole, tricyclazole, and isocarbophos are figured out, and the band assignments for major characteristic peaks are listed in Table . Specifically, the major four characteristic peaks of paraquat at wavenumber of 840 cm −1 , 1,191 cm −1 , 1,295 cm −1 , and 1,646 cm −1 are assigned to the vibrations of C‐N stretching, C=C deformation, C‐C deformation, and C=N stretching, respectively . In the case of thiabendazole, the prominent peaks at wavenumber of 1,575 cm −1 , 1,010 cm −1 , 1,279 cm −1 , and 1,575 cm −1 arise from the complex skeletal vibration modes, and the detailed assignments are demonstrated in Table .…”

“…Specifically, the major four characteristic peaks of paraquat at wavenumber of 840 cm −1 , 1,191 cm −1 , 1,295 cm −1 , and 1,646 cm −1 are assigned to the vibrations of C-N stretching, C=C deformation, C-C deformation, and C=N stretching, respectively. [25,26] In the case of thiabendazole, the prominent peaks at wavenumber of 1,575 cm −1 , 1,010 cm −1 , 1,279 cm −1 , and 1,575 cm −1 arise from the complex skeletal vibration modes, [27,28] and the detailed assignments are demonstrated in Table 1. The main characteristic vibration bands of tricyclazole stem from the C-N-C bending (429 cm −1 ), C-C bending (561 cm −1 ), C-S-C bending (595 cm −1 ), C=C stretching (974 cm −1 ), and C-N stretching (1,310 cm −1 and 1,374 cm −1 ), respectively.…”

Trace analysis of organic compounds in foods with surface‐enhanced Raman spectroscopy: Methodology, progress, and challenges

“…When metallic nanoparticle colloid is involved, similar to that for the substrate with a nanostructured surface, the colloid could be deposited onto a glass slide or other sample holder and dried first; next, the analyte is dropped on top of the assembled nanoparticles (Pei et al., ; Y. Zhang et al., ). However, most often, colloidal nanoparticles and the analyte solution or sample extract is mixed, and then a drop of this mixture is deposited on a sample holder; following this, SERS spectra are collected from multiple spots of the dried droplet (Figure 3b) (Luo et al., ; Ou et al., ; Pei et al., ; Wijaya et al., ; Y. Zhang et al., ). This “dried colloid” method is simple and widely applied in analyzing food or other samples, but the distribution of the target compound and nanoparticles on the surface of a sample holder could be very complicated, depending on the surface properties (for example, charge) of both nanoparticles and the target molecules (Culha, ).…”

“…However, since SERS effect is essentially a monolayer effect, if the analyte concentration is too high leading to the saturation of the monolayer, then the linearity between analyte concentration and instrumental response no longer applies (Bell & Sirimuthua, ; McNay et al., ). More complicated chemometric approaches such as partial least square regression and artificial neural networks have been used for SERS spectral data analysis (He, Chen, & Labuza, ; Huang, Kangas, & Rasco, ; Lai et al., ; Luo et al., ; ; Mandrile, Giovannozzi, Durbiano, Martra, & Rossi, ; Pan et al., ). These chemometric approaches utilizing full spectrum instead of a single peak are widely applied for NIR spectral data analysis and their underlying algorithm and applications are well studied and documented.…”

“…The application of SERS for quantifying trace compounds is generally unsatisfactory to date due to the difficulties of obtaining reproducible SERS spectra, although there are some reported studies indicating the potential of employing SERS for quantitative analysis. A simple way for quantitative analysis with SERS was based upon a linear relationship between analyte concentrations within a specific range and their corresponding SERS characteristic peak intensities (Fan et al., ; Luo et al., ; Zhao et al., ). However, since SERS effect is essentially a monolayer effect, if the analyte concentration is too high leading to the saturation of the monolayer, then the linearity between analyte concentration and instrumental response no longer applies (Bell & Sirimuthua, ; McNay et al., ).…”