Line-Scan Macro-scale Raman Chemical Imaging for Authentication of Powdered Foods and Ingredients

Rapid determination of thiram on apple using a flexible bacterial cellulose-based SERS substrate

A flexible nanocomposite composed of bacterial cellulose (BC) and gold nanoparticles (AuNPs) was developed as a SERS substrate to determine thiram on apple surface by two collection methods namely "paste-and-peel" and "wiping". Enhancement factor of this SERS substrate for sensing thiram residues was determined to be 2.8 × 10⁵. Compared to the benchtop Raman spectrometer, portable Raman spectroscopic device showed a lower sensitivity towards thiram residues with limit of detection at 0.98 ppm, satisfying maximum residue level of thiram on apple required by both Europe and America. A good linear correlation of SERS peak intensity at 1368 cm^-1 and different concentrations of thiram (1-50 ppm) revealed a coefficient up to 0.99. This flexible BC-based SERS substrate has a great analytical performance in sensitivity, reproducibility and stability, and is suitable for rapid detection (<8 min) and quantitative analysis of pesticides on food surface.

Progress on aptamer-based SERS sensors for food safety and quality assessment: methodology, current applications and future trends

It is well known that food safety has aroused extensive attentions from governments to researchers and to food industries. As a versatile technology based on molecular interactions, aptamer sensors which could specifically identify a wide range of food contaminants have been extensively studied in recent years. Surface-enhanced Raman spectroscopy integrated aptamer combines the advantages of both technologies, not only in the ability to specifically identify a wide range of food contaminants, but also in the ultra-high sensitivity, simplicity, portable and speed. To provide beneficial insights into the evaluation techniques in the field of food safety, we offer a comprehensive review on the design strategies for aptamer-SERS sensors in different scenarios, including non-nucleic acid amplification methods ("on/off" mode, sandwich mode, competition model and catalytic model) and nucleic acid amplification methods (hybridization chain reaction, rolling circle amplification, catalytic hairpin assembly). Meanwhile, a special attention is paid to the application of aptamer-SERS sensors in biological (foodborne pathogenic, bacteria and mycotoxins) and chemical contamination (drug residues, metal ions, and food additives) of food matrix. Finally, the challenges and prospects of developing reliable aptamer-SERS sensors for food safety were discussed, which are expected to offer a strong guidance for further development and extended applications.

Recent Developments in Surface-Enhanced Raman Spectroscopy and Its Application in Food Analysis: Alcoholic Beverages as an Example

Surface-enhanced Raman spectroscopy (SERS) is an emerging technology that combines Raman spectroscopy and nanotechnology with great potential. This technology can accurately characterize molecular adsorption behavior and molecular structure. Moreover, it can provide rapid and sensitive detection of molecules and trace substances. In practical application, SERS has the advantages of portability, no need for sample pretreatment, rapid analysis, high sensitivity, and ‘fingerprint’ recognition. Thus, it has great potential in food safety detection. Alcoholic beverages have a long history of production in the world. Currently, a variety of popular products have been developed. With the continuous development of the alcoholic beverage industry, simple, on-site, and sensitive detection methods are necessary. In this paper, the basic principle, development history, and research progress of SERS are summarized. In view of the chemical composition, the beneficial and toxic components of alcoholic beverages and the practical application of SERS in alcoholic beverage analysis are reviewed. The feasibility and future development of SERS are also summarized and prospected. This review provides data and reference for the future development of SERS technology and its application in food analysis.

Highly Ordered Polymer Nanostructures via Solvent On-Film Annealing for Surface-Enhanced Raman Scattering

Surface-enhanced Raman scattering (SERS) has been a useful sensing technique, in which inelastic light scattering can be significantly enhanced by absorbing molecules onto rough metal surfaces or nanoparticles. Although many methods have been developed to prepare SERS substrates, it is still highly desirable and challenging to design SERS substrates, especially with highly ordered and controlled three-dimensional (3D) structures. In this work, we develop novel SERS substrates with regular volcano-shaped polymer structures using the versatile solvent on-film annealing method. Polystyrene (PS) nanospheres are first synthesized by surfactant-free emulsion polymerization and assembled on poly(methyl methacrylate) (PMMA) films. After annealing in acetic acid vapors, PMMA chains are selectively swollen and wet the surfaces of the PS nanospheres. By selectively removing the PS nanospheres using cyclohexane, volcano-shaped PMMA films can be obtained. Compared with flat PMMA films with water contact angles of ∼74°, volcano-shaped PMMA films exhibit higher water contact angles of ∼110° due to the sharp features and rough surfaces. The volcano-shaped PMMA films are then coated with gold nanoparticles (AuNPs) as SERS substrates. Using rhodamine 6G as the probe molecules, the SERS results show that the Raman signals of the volcano-shaped PMMA/AuNP hybrid substrates are much higher than those of the pristine PMMA films and PMMA films with AuNPs. For the volcano-shaped PMMA/AuNP hybrid substrates using 400 nm PS nanospheres, a high enhancement factor (EF) value of ∼1.12 × 10⁵ with a detection limit of 10^-8 M is obtained in a short integration time of 1 s. A linear calibration line with an R² value of 0.918 is also established, demonstrating the ability to determine the concentrations of the analytes. This work offers significant insight into developing novel SERS substrates, which is crucial for improving the detection limits of analytes.

Application of surface-enhanced Raman spectroscopy in fast detection of toxic and harmful substances in food

Surface-enhanced Raman spectroscopy (SERS) is being considered as a powerful technique in the area of food safety due to its rapidity, sensitivity, portability, and non-destructive features. This review aims to provide a comprehensive understanding of SERS applications in fast detection of toxic and harmful substances in food matrix. The enhancement mechanism of SERS, classification of active substrates, detection methods, and their advantages and disadvantages are briefly discussed in the review. The latest research progress of fast SERS detection of food-borne pathogens, mycotoxins, shellfish toxins, illegal food additives, and drug residues are highlighted in sections of the review. According to the current status of SERS detection of food-derived toxic and harmful substances, the review comes up with certain problems to be urgently resolved in SERS and brings up the perspectives on the future directions of SERS based biosensors.

Improving Sensitivity in Raman Imaging for Thin Layered and Powdered Food Analysis Utilizing a Reflection Mirror

Raman imaging has been proven to be a powerful analytical technique for the characterization and visualization of chemical components in a range of products, particularly in the food and pharmaceutical industries. The conventional backscattering Raman imaging technique for the spatial analysis of a deep layer suffers from the presence of intense fluorescent and Raman signals originating from the surface layer which mask the weaker subsurface signals. Here, we demonstrated the application of a new reflection amplifying method using a background mirror as a sample holder to increase the Raman signals from a deep layer. The approach is conceptually demonstrated on enhancing the Raman signals from the subsurface layer. Results show that when bilayer samples are scanned on a reflection mirror, the average signals increase 1.62 times for the intense band at 476 cm⁻¹ of starch powder, and average increases of 2.04 times (for the band at 672 cm⁻¹) for a subsurface layer of high Raman sensitive melamine powder under a 1 mm thick teflon sheet. The method was then applied successfully to detect noninvasively the presence of small polystyrene pieces buried under a 2 mm thick layer of food powder (a case of powdered food adulteration) which otherwise are inaccessible to conventional backscattering Raman imaging. In addition, the increase in the Raman signal to noise ratio when measuring samples on a mirror is an important feature in many applications where high-throughput imaging is of interest. This concept is also applicable in an analogous manner to other disciplines, such as pharmaceutical where the Raman signals from deeper zones are typically, substantially diluted due to the interference from the surface layer.

Fabrication of gold nanorods for SERS detection of thiabendazole in apple

Thiabendazole (TBZ) is a kind of pesticide that is widely used in agriculture, and its residue may pose a threat to human health. In order to measure TBZ residues in food samples, a surface-enhanced Raman spectroscopy (SERS) method combined with a homogeneous and reusable gold nanorods (GNR) array substrate was proposed. GNR with a high uniformity was synthesized and then applied to the self-assembly of a GNR vertically aligned array. The relative standard deviation (RSD) of the array for SERS could reach 15.4%, and the array could be reused for more than seven times through the treatment of plasma etching. A logarithmic correlation between TBZ concentration and Raman intensity was obtained, with the best determination coefficient (R²) and the corresponding limit of detection (LOD) of 0.991 and 0.037 mg/L in methanol solution, and 0.980 and 0.06 ppm in apple samples, respectively. The recoveries of TBZ in apple samples ranged from 76% to 107%. This study provided a rapid and sensitive approach for detecting TBZ in apples based on SERS coupled with GNR array substrate, showing great potential for analyzing other trace contaminants in food matrices.

Double strand DNA functionalized Au@Ag Nps for ultrasensitive detection of 17β-estradiol using surface-enhanced raman spectroscopy

A detection method for 17β-estradiol (E2) using surface-enhanced Raman scattering (SERS)-based aptamer sensor was presented. Raman reporter molecule Cy3 labeled E2-aptamer and DNA functionalized gold-silver core-shell nanoparticles (Au@Ag CS NPs) offered SERS with high sensitivity and selectivity. Based on the fabricated double strand DNA-immobilized gold-silver core-shell nanoparticles (Au@Ag NPs), SERS signal intensity of Raman reporter changed with the number of Cy3-labeled aptamer attached to the core-shell nanoparticles due to the strong binding affinity between the aptamers and E2 with different concentrations. A wide linear range from 1.0 × 10^-13 to 1.0 × 10^-9 was obtained for the detection of E2, with a low detection limit of 2.75 fM. This proposed method showed highly sensitive and selective for detecting E2, and could be used to determine E2 in actual samples.

Fast quantitative fluorescence authentication of milk powder and vanillin by a line-scan hyperspectral system

We present a fast hyperspectral line-scan fluorescence imaging system to verify the feasibility of quantitative fluorescence authentication of powders. Vanillin, which is restricted for use in milk powder, especially in milk powder for infants, is mixed with milk powder in different mass concentrations (5%, 10%, 30%, 50%, 70%, and 90%). Mixed powders are located on a motorized linear stage. A 405 nm line laser is utilized to excite the fluorescence of the sample. Based on galvo scanning, we can generate a laser line with high spatial resolution and high-intensity density on the samples. An imaging spectrometer with a complementary metal-oxide semiconductor (CMOS) camera as detector is built. The spectral range of the spectrometer is 365-810 nm, with about 1 nm spectral resolution. One snapshot of the CMOS can acquire the fluorescent spatial and spectral information of a line region in 100 ms. By scanning the motorized linear stage, we obtain the fluorescence hypercube of the sample. A 100×1926×1216 hypercube, which covers an area of 15  mm×5  mm, is obtained in 50 s. The imaging speed can be enhanced further by increasing the intensity of the excitation laser and the sensitivity of the area camera. Fully constrained least squares, a linear spectral mixture analysis, is utilized to analyze the hypercube obtained by our homemade imaging spectrometer, thus obtaining the pixel concentration of vanillin in each mixed powder. Linear regression analysis is used for the pixel concentration and mass concentration of vanillin. A linear relationship with coefficient of determination R² equal to one is observed, which demonstrates the capability of fluorescence hyperspectral quantitative analysis in powders.

Raman Hyperspectral Imaging for Detection of Watermelon Seeds Infected with Acidovorax citrulli

The bacterial infection of seeds is one of the most important quality factors affecting yield. Conventional detection methods for bacteria-infected seeds, such as biological, serological, and molecular tests, are not feasible since they require expensive equipment, and furthermore, the testing processes are also time-consuming. In this study, we use the Raman hyperspectral imaging technique to distinguish bacteria-infected seeds from healthy seeds as a rapid, accurate, and non-destructive detection tool. We utilize Raman hyperspectral imaging data in the spectral range of 400–1800 cm⁻¹ to determine the optimal band-ratio for the discrimination of watermelon seeds infected by the bacteria Acidovorax citrulli using ANOVA. Two bands at 1076.8 cm⁻¹ and 437 cm⁻¹ are selected as the optimal Raman peaks for the detection of bacteria-infected seeds. The results demonstrate that the Raman hyperspectral imaging technique has a good potential for the detection of bacteria-infected watermelon seeds and that it could form a suitable alternative to conventional methods.

Single-shot chemical detection and identification with compressed hyperspectral Raman imaging

Raman imaging is a powerful method to identify and detect chemicals, but the long acquisition time required for full spectroscopic Raman images limits many practical applications. Compressive sensing and compressed ultrafast photography have recently demonstrated the acquisition of multi-dimensional data sets with single-shot detection. In this Letter, we demonstrate the utilization of compressed sensing for single-shot compressed Raman imaging. In particular, we use this technique to demonstrate the identification of two similarly white substances in one image via the recovered two-dimensional array of Raman spectra. This technique can be further extended by coupling the compressed sensing apparatus with a microscope for compressed hyperspectral imaging microscopy.

Detection and quantification of adulterants in milk powder using a high-throughput Raman chemical imaging technique

Milk is a vulnerable target for economically motivated adulteration. In this study, a line-scan high-throughput Raman imaging system was used to authenticate milk powder. A 5 W 785 nm line laser (240 mm long and 1 mm wide) was used as a Raman excitation source. The system was used to acquire hyperspectral Raman images in a wave number range of 103-2881 cm^-1 from the skimmed milk powder mixed with two nitrogen-rich adulterants (i.e., melamine and urea) at eight concentrations (w/w) from 50 to 10,000 ppm. The powdered samples were put in sample holders with a surface area of 150 ×100 mm and a depth of 2 mm for push-broom image acquisition. Varying fluorescence signals from the milk powder were removed using a correction method based on adaptive iteratively reweighted penalised least squares. Image classifications were conducted using a simple thresholding method applied to single-band fluorescence-corrected images at unique Raman peaks selected for melamine (673 cm^-1) and urea (1009 cm^-1). Chemical images were generated by combining individual binary images of melamine and urea to visualise identification, spatial distribution and morphological features of the two adulterant particles in the milk powder. Limits of detection for both melamine and urea were estimated in the order of 50 ppm. High correlations were found between pixel concentrations (i.e., percentages of the adulterant pixels in the chemical images) and mass concentrations of melamine and urea, demonstrating the potential of the high-throughput Raman chemical imaging method for the detection and quantification of adulterants in the milk powder.