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In order to prompt the appearance of the shrimp color, sodium metabisulfite is frequently added in shrimp processing, which is, however, prohibited in China and many other countries. This study aimed to establish a surface-enhanced Raman spectroscopy (SERS) method for screening sodium metabisulfite residues on shrimp surfaces, in a non-destructive manner. The analysis was carried out using a portable Raman spectrometer jointly with copy paper loaded with silver nanoparticles as the substrate material. The SERS response of sodium metabisulfite gives two fingerprint peaks at 620 (strong) and 927 (medium) cm−1, respectively. This enabled unambiguous confirmation of the targeted chemical. The sensitivity of the SERS detection method was determined to be 0.1 mg/mL, which was equal to residual sodium metabisulfite on the shrimp surface at 0.31 mg/kg. The quantitative relationship between the 620 cm−1 peak intensities and the concentrations of sodium metabisulfite was established. The linear fitting equation was y = 2375x + 8714 with R2 = 0.985. Reaching an ideal balance in simplicity, sensitivity, and selectivity, this study demonstrates that the proposed method is ideally suitable for in-site and non-destructive screening of sodium metabisulfite residues in seafood. [ABSTRACT FROM AUTHOR]

With the continuous development of China's economy and society, people and the government have higher and higher requirements for food safety. Testing for food dopants and toxins can prevent the occurrence of various adverse health phenomena in the world's population. By deploying new and powerful sensors that enable rapid sensing processes, the food industry can help detect trace adulteration and toxic substances. At present, as a common food safety detection method, lateral flow immunochromatography (LFI) is widely used in food safety testing, environmental testing and clinical medical treatment because of its advantages of simplicity, speed, specificity and low cost, and plays a pivotal role in ensuring food safety. This paper mainly focuses on the application of lateral flow immunochromatography and new technologies combined with test strips in food safety detection, such as aptamers, surface-enhanced Raman spectroscopy, quantum dots, electrochemical test strip detection technology, biosensor test strip detection, etc. In addition, sensing principles such as fluorescence resonance energy transfer can also more effective. Different methods have different characteristics. The following is a review of the application of these technologies in food safety detection. [ABSTRACT FROM AUTHOR]

A surface enhanced Raman spectroscopy (SERS) substrate with high sensitivity for the rapid determination of pesticide residues was developed by combining silver nanoparticles (AgNPs) and a fibrous swab. The SERS substrate was prepared simply by forming a SERS-active area on the section of fibrous swab and centrifuge tube with a soak-absorb approach. Rhodamine 6 G (R6G), a common SERS probe molecule, was used for performance characterization of the prepared SERS substrate that was shown to have high sensitivity, good stability and good reproducibility. Due to its good flexibility, the prepared SERS substrate was used to wipe contaminated surfaces for residue extraction. High sensitivity for detecting trace-level pesticides was verified for thiram. The limits of detection (LODs) for thiram on apple, grape and eggplant epidermis were calculated to be as low as 0.5313, 0.5768, and 0.5495 ng·cm−2, respectively, nearly 2 orders of magnitude below the maximum residue limit (MRL) for pesticide in food issued by the National Food Safety Standard of China. In addition, there was a linear relationship between the SERS intensity and the concentration of thiram in these three samples, indicating the good potential of this substrate for quantitative SERS analysis. [ABSTRACT FROM AUTHOR]

• A food safety screening method using a portable Raman spectrometer is described. • Adhesive tapes were examined and used as sampling media to recover analytes. • The tape lifting sampling efficiencies on different surfaces were explored. • Ag NPs were optimized for the best SERS performance. • Triazophos was successfully detected on fruit peels with high sensitivity. In this work, we report a simple and rapid surface-enhanced Raman scattering (SERS) method for the screening of pesticide residues on fruit peels using a portable Raman spectrometer. Adhesive tapes were used as the sampling media; the effectiveness of different tape brands was examined. Collection efficiencies were found to be 60.2 ± 7.6%, 54.3 ± 5.0%, and 52.3 ± 9.0% on glass, aluminum foil, and fruit peels, respectively. SERS was achieved by applying silver nanoparticles (Ag NPs) to the surface of the tape after analyte collection. Preparation of the Ag NPs was optimized for pesticide detection. The limit of detection of triazophos on apple peels was 25 ng/cm2 with the portable Raman spectrometer. Considering the least favorable conditions, the calculated detection limit was 0.0225 mg/kg, which is an order of magnitude less than the maximum residue limit (MRL, 0.2 mg/kg) in China. The method is sufficiently sensitive for use in field analysis. [ABSTRACT FROM AUTHOR]

Raman spectroscopy exhibits potential as a tool for identifying the chemical composition of substances and has witnessed a growing application in urological oncology. This study undertook a bibliometric analysis to chart the present state and future prospects of Raman spectroscopy applications in urological tumors. The present study retrieved literature on the utilization of Raman spectroscopy in urological oncology from the Science Citation Index Expanded of Web of Science Core Collection, spanning from its inception to June 2023. Data from included studies were analyzed using CiteSpace, Python, and Excel. Our study examined 897 articles from 65 countries and identified a significant exponential growth in annual publications. The USA and China were prominent contributors to this field, with high publication rates and funding agencies. Shanghai Jiao Tong University emerged as the most influential institution. The journals Analytical Chemistry and Analyst were found to be the most productive. Our keyword analysis revealed an intense interest for "gold nanoparticle" and "pathology," with the most recent bursts occurring for "surface-enhanced Raman scattering (SERS)," "biomarkers," and "prostate specific antigen." As a detection tool, Raman spectroscopy holds the potential to assist in the identification, management, and prognostication of urological tumors. Notably, adjuvant diagnosis and prognosis evaluation based on SERS of tumor markers is a hot research topic. These findings offer valuable insights into the current state of Raman spectroscopy research in urological oncology, which could inform future studies and clinical practice. [ABSTRACT FROM AUTHOR]

Chlorpyrifos (CPF) and 2,4-dichlorophenoxyacetic acid (2,4-D) are insecticides and herbicides which has been widely used on farms. However, CPF and 2,4-D residues on corps can bring high risks to human health. Accurate detection of pesticide residues is important for controlling health risks caused by CPF and 2,4-D. Therefore, we developed a fast, sensitive, economical, and lossless surface-enhanced Raman spectroscopy (SERS)-based method for pesticide detection. It can rapidly and simultaneously determine the CPF and 2,4-D mixed pesticide residues on an apple surface at a minimum of 0.001 mg L−1 concentration, which is far below the pesticide residue standard in China and the EU. The limits of detection reach down to 1.28 × 10−9 mol L−1 for CPF and 2.47 × 10−10 mol L−1 for 2,4-D. The limits of quantification are 4.27 × 10−9 mol L−1 and 8.23 × 10−10 mol L−1 for CPF and 2,4-D. This method has a great potential for the accurate detection of pesticide residues, and may be applied to other fields of agricultural products and food industry. [ABSTRACT FROM AUTHOR]

[Display omitted] • GA-PLS, UVE-PLS, VCPA-PLS and CARS-PLS were comparatively investigated for CP detection. • CARS-PLS model achieved optimum results, the RPD was 4.87. • A SERS-based method for CP was developed with a LOD of 0.01 μg/mL. • The LODs found were lower than the People's Republic of China set the standard of CP in pollution-free rice. Due to the continuous development and progress of society and more and more attention to the quality and safety of food, rapid testing of pesticides in food is of great significance. In this paper, surface-enhanced Raman spectroscopy (SERS) and chemometric algorithms were employed collectively to quantify chlorpyrifos (CP) residues in rice samples. The SERS spectra from different concentrations (0.01–1000 μg/mL) of CP were collected using AgNPs-deposited-ZnO nanoflower (NFs)-like nanoparticles (Ag@ZnO NFs) SERS sensor. Four quantitative chemometric models for CP were comparatively studied, and the competitive adaptive reweighted sampling-partial least squares model achieved the best prediction and practical applicability for predicting CP levels with a limit of detection of 0.01 µg/mL. The results of the student's t -test showed no significant difference between this method and high-performance liquid chromatography (HPLC), and good relative standard deviation (RSD) indicated that this method could be used for the detection of CP in rice. [ABSTRACT FROM AUTHOR]

Salmonella is a prevalent pathogen causing serious morbidity and mortality worldwide. There are over 2600 serovars of Salmonella. Among them, Salmonella Enteritidis, Salmonella Typhimurium, and Salmonella Paratyphi were reported to be the most common foodborne pathogenic serovars in the EU and China. In order to provide a more efficient approach to detect and distinguish these serovars, a new analytical method was developed by combining surface-enhanced Raman spectroscopy (SERS) with multi-scale convolutional neural network (CNN). We prepared 34-nm gold nanoparticles (AuNPs) as the label-free Raman substrate, measured 1854 SERS spectra of these three Salmonella serovars, and then proposed a multi-scale CNN model with three parallel CNNs to achieve multi-dimensional extraction of SERS spectral features. We observed the impact of the number of iterations and training samples on the recognition accuracy by changing the ratio of the number of the training and testing sets. By comparing the calculated data with experimental one, it was shown that our model could reach recognition accuracy more than 97%. These results indicate that it was not only feasible to combine SERS spectroscopy with multi-scale CNN for Salmonella serotype identification, but also for other pathogen species and serovar identifications. [ABSTRACT FROM AUTHOR]

The safety of cosmetics attributing to the illegal addition of antibiotics for quick effect is a big concern nowadays. Nitrofurans, one of commonly added illegal antibiotics, are strictly banned in cosmetics in China. It is still a great challenge for the rapid and precise analysis of trace nitrofurans when facing various cosmetics with complicated matrices. Surface‐enhanced Raman spectroscopy (SERS) is emerging as a novel rapid on‐site analytical technique. In this work, an accurate SERS method was developed for the rapid analysis of trace nitrofurantoin in various cosmetics by use of nanoarrayed hydroxyl polystyrene (PS‐OH)‐based substrate. A series of characterizations indicated the successful synthesis of Au@PS‐OH substrate and the uniform distribution of gold nanoparticles on the substrate surface. The SERS substrate revealed good selectivity and reproducibility with an enhancement factor of 2.6×104. Finally, an analytical method for the determination of nitrofurantoin in cosmetics was established by SERS using Au@PS‐OH substrate coupling with efficient sample preparation process. It was satisfied that trace nitrofurantoin could be actually detected and quantified to be 1.77 and 7.74 mg/L in a mouthwash and rose‐mist sample, respectively, with good recoveries of 86.8‐106% and relative standard deviations of 0.9‐2.9%. The comparable analytical results for real samples were achieved by the traditional high‐performance liquid chromatography (HPLC) method, which validated the reliability of the proposed method. It is expected that this SERS method has great potential for the rapid and on‐site analysis of trace additives in cosmetics. [ABSTRACT FROM AUTHOR]