Simultaneous, Label-Free and High-throughput SERS Detection of Multiple Pesticides on Ag@Three-Dimensional Silica Photonic Microsphere Array

Surface control in the adsorption of tebuthiuron on modified silver surfaces tracked by surface-enhanced Raman scattering spectroscopy

The vibrational assignment of the Raman and surface-enhanced Raman scattering (SERS) spectra of the herbicide tebuthiuron (TBH) was accomplished, which allowed unprecedented propositions for adsorption geometries on the surface of silver nanoparticles (AgNP). Ascribed SERS features allowed suggesting that the adsorption occurred through nitrogen atoms of thiadiazole group, since intense band shift assigned to ring mode was marking of the coordination with the metallic surface. AgNP were treated with different surface modifiers that leaded to substantial changes in TBH adsorption geometries. Spectral changes, as the enhancement of out-of-plane ring modes, were indicative of the presence of tilted thiadiazole geometries in relation to the silver surface. Density Functional Theory (DFT) calculations from TBH molecules, in isolation and in interaction with ten-atom cluster of silver leaded to obtain theoretical spectra that gave support to interpret experimental Raman and SERS spectra.

Regenerated SERS substrate based on Ag/AuNPs-TiO2-oxidized carbon cloth for detection of imidacloprid

Imidacloprid (IMI) are widely used in modern tea industry for pest control, but IMI residues pose a great threat to human health. Herein, we propose a regeneration metal-semiconductor SERS substrate for IMI detection. We fabricated the SERS sensor through the in-situ growth of a nano-heterostructure incorporating a semiconductor (TiO2) and plasmonic metals (Au, Ag) on oxidized carbon cloth (OCC). Leveraging the high-density hot spots, the formed Ag/AuNPs-TiO2-OCC substrate exhibits higher enhancement factors (1.92 × 108) and uniformity (RSD = 7.68%). As for the detection of IMI on the substrate, the limit of detection was lowered to 4.1 × 10-6 μg/mL. With a hydrophobic structure, the Ag/AuNPs-TiO2-OCC possessed excellent self-cleaning performance addressing the limitation of single-use associated with traditional SERS substrates, as well as the degradation capability of the substrate under ultraviolet (UV) light. Accordingly, Ag/AuNPs-TiO2-OCC showcases outstanding SERS sensing and regenerating properties, making it poised for extensive application in the field of food safety assurance.

Highly sensitive SERS detection of melamine based on 3D Ag@porous silicon photonic crystal

The stability, reproducibility and engineering of SERS substrate faces a great challenge in melamine SERS assay. In this work, a simple, highly sensitive, stable and cost-efficient SERS detection platform for melamine was established based on its Raman fingerprints spectrum. The Ag@ porous silicon photonic crystal (Ag@PPC) was prepared as the 3D SERS substrate by electrochemical etching and magnetron sputter technology. The main influence factors for the preparation of SERS substrate were investigated in detail. The analytical enhancement factor of the 3D SERS substrate can reach to 2.6 × 108. The 3D SERS detection platform showed a wide linear detection range of 10-4∼10 mg L-1 and a low limit of detection of 0.1 μg L-1 for melamine. Moreover, such detection platform showed good stability, high reproducibility and high recovery rates for melamine. The 3D Ag@PPC SERS substrate can be easily prepared and engineered, displaying a great potential application in food safety field.

Raman silent region - based method for detection of pesticides with cyano group

Based on the fact that not all chemical substances possess good Raman signals, this article focuses on the Raman silent region signals of pesticides with cyano group. Under the optimized conditions of methanol-water (1:1, v/v) as the solvent, irradiation at 302 nm light source for 20 min, and the use of 0.5 mol/L KI as the aggregating agent, Surface-enhanced Raman spectroscopy (SERS) method for azoxystrobin detection was developed by the Raman silent region signal of 2230 cm-1, and verified by detecting the spiked grapes with different concentrations of azoxystrobin. Other four pesticides with cyano group also could be identified at the peak of 2180 cm-1, 2205 cm-1, 2125 cm-1, and 2130 cm-1 for acetamiprid, phoxim, thiacloprid and cymoxanil, respectively. When azoxystrobin or acetamiprid was mixed respectively with chlorpyrifos without cyano group, their SERS signals in the Raman silent region of chlorpyrifos were not interfered, while mixed with cymoxanil in different ratios (1:4, 1:1 and 4:1), respectively, each two pesticides with cyano group could be distinguished by the changes in the Raman silent region. In further, four pesticides with or without cyano group were mixed together in 1:1:1:1 (acetamiprid, cymoxanil, azoxystrobin chlorpyrifos), and each pesticide still could be identified even at 0.5 mg/L. The results showed that the SERS method combined with UV irradiation may provide a new way to monitor the pesticides with C≡N performance in the Raman silent region without interference from the food matrix.

Towards solving the reproducibility crisis in surface-enhanced Raman spectroscopy-based pesticide detection

Growing concerns about pesticide residues in agriculture are pushing the scientific community to develop innovative and efficient methods for detecting these substances at low concentrations down to the molecular level. In this context, surface-enhanced Raman spectroscopy (SERS) is a powerful analytical method that has so far already undergone some validation for its effectiveness in pesticide detection. However, despite its great potential, SERS faces significant difficulties obtaining reproducible and accurate pesticide spectra, particularly for some of the most widely used pesticides, such as malathion, chlorpyrifos, and imidacloprid. Those inconsistencies can be attributed to several factors, such as interactions between pesticides and SERS substrates and the variety of substrates and solvents used. In addition, differences in the equipment used to obtain SERS spectra and the lack of standards for control experiments further complicate the reproducibility and reliability of SERS data. This review systematically discusses the problems mentioned above, including a comprehensive analysis of the challenges in precisely evaluating SERS spectra for pesticide detection. We not only point out the existing limitations of the method, which can be traced in previous review works, but also offer practical recommendations to improve the quality and comparability of SERS spectra, thereby expanding the potential applications of the method in such an essential field as pesticide detection.

Dialdehyde starch-enclosed silver nanoparticles substrate with controlled-release "hotspots" for ultrasensitive SERS detection of thiabendazole

Pesticide residues have long been a major concern for food safety. In this study, a dialdehyde starch-encapsulated silver nanoparticles composite with controlled-release "hotspots" was developed as a surface-enhanced Raman scattering (SERS) substrate. At room temperature, most of the Ag NPs were encapsulated in dialdehyde starch, which is beneficial for improving stability, and when heated to the gelatinization point, Ag NPs are completely released and abundant hot spots are formed. We demonstrated sensitive detection of thiabendazole (TBZ) in or on the surface of an apple by means of two ways, i.e., detecting the analyte in solution after pretreatment and in-situ detecting the analyte by using a flexible paper-based substrate. The results showed that the detection limits of TBZ by the two ways were 0.052 ppm and 0.051 ppm respectively, and the recoveries of TBZ range from 96.80 % to 105.46 %. Overall, this SERS substrate shows great potential for pesticide residue detection in food.

Highly Sensitive Microarray Immunoassay for Multiple Mycotoxins on Engineered 3D Porous Silicon SERS Substrate with Silver Nanoparticle Magnetron Sputtering

A high-throughput, rapid, and highly sensitive surface-enhanced Raman spectroscopy (SERS) microarray for screening multiple mycotoxins has been developed on a three-dimensional silver nanoparticle porous silicon (3D AgNP-Psi) SERS substrate, which was easy to be engineered by electrochemical etching and magnetron sputtering technology. The etching current density, etching waveform, and target material for magnetron sputtering have been investigated to obtain an optimal 3D SERS substrate. The optimized 3D AgNP-Psi SERS substrate showed an enhancement factor of 2.3 × 107 at 400 mA/cm2 constant current density etching for 20 s and Ag target magnetron sputtering for 200 nm thickness on the surface of Psi. The simulation electric field distribution showed the near-field enhancement can reach 3× higher than that of AuNPs. A protein microarray has been designed to screen multiple mycotoxins by AuNP Raman tags and a competitive immunoassay protocol on the surface of the 3D SERS substrate. The SERS protein microarray displayed wide linear detection ranges of 0.001-100 ng/mL for ochratoxin A, 0.01-100 ng/mL for aflatoxin B1, 0.001-10 ng/mL for deoxynivalenol, along with pg/mL low limit of detection, good recovery rates, repeatability, and reproducibility. The 3D SERS protein microarray is easily engineered and has a great potential application in medicine, environment, and food industry fields.

Developments in food neonicotinoids detection: novel recognition strategies, advanced chemical sensing techniques, and recent applications

Neonicotinoid insecticides (NEOs) are a new class of neurotoxic pesticides primarily used for pest control on fruits and vegetables, cereals, and other crops after organophosphorus pesticides (OPPs), carbamate pesticides (CBPs), and pyrethroid pesticides. However, chronic abuse and illegal use have led to the contamination of food and water sources as well as damage to ecological and environmental systems. Long-term exposure to NEOs may pose potential risks to animals (especially bees) and even human health. Consequently, it is necessary to develop effective, robust, and rapid methods for NEOs detection. Specific recognition-based chemical sensing has been regarded as one of the most promising detection tools for NEOs due to their excellent selectivity, sensitivity, and robust interference resistance. In this review, we introduce the novel recognition strategies-enabled chemical sensing in food neonicotinoids detection in the past years (2017-2023). The properties and advantages of molecular imprinting recognition (MIR), host-guest recognition (HGR), electron-catalyzed recognition (ECR), immune recognition (IR), aptamer recognition (AR), and enzyme inhibition recognition (EIR) in the development of NEOs sensing platforms are discussed in detail. Recent applications of chemical sensing platforms in various food products, including fruits and vegetables, cereals, teas, honey, aquatic products, and others are highlighted. In addition, the future trends of applying chemical sensing with specific recognition strategies for NEOs analysis are discussed.

Food Safety Issues in the Oltrepò Pavese Area: A SERS Sensing Perspective

Handly and easy-to-use optical instrumentation is very important for food safety monitoring, as it provides the possibility to assess law and health compliances at every stage of the food chain. In particular, the Surface-enhanced Raman Scattering (SERS) method appears highly promising because the intrinsic drawback of Raman spectroscopy, i.e., the natural weakness of the effect and, in turn, of the signal, is overcome thanks to the peculiar interaction between laser light and plasmonic excitations at the SERS substrate. This fact paved the way for the widespread use of SERS sensing not only for food safety but also for biomedicine, pharmaceutical process analysis, forensic science, cultural heritage and more. However, the current technological maturity of the SERS technique does not find a counterpart in the recognition of SERS as a routine method in compliance protocols. This is mainly due to the very scattered landscape of SERS substrates designed and tailored specifically for the targeted analyte. In fact, a very large variety of SERS substrates were proposed for molecular sensing in different environments and matrices. This review presents the advantages and perspectives of SERS sensing in food safety. The focus of the survey is limited to specific analytes of interest for producers, consumers and stakeholders in Oltrepò Pavese, a definite regional area that is located within the district of Pavia in the northern part of Italy. Our attention has been addressed to (i) glyphosate in rice fields, (ii) histamine in a world-famous local product (wine), (iii) tetracycline, an antibiotic often detected in waste sludges that can be dangerous, for instance in maize crops and (iv) Sudan dyes-used as adulterants-in the production of saffron and other spices, which represent niche crops for Oltrepò. The review aims to highlight the SERS performance for each analyte, with a discussion of the different methods used to prepare SERS substrates and the different reported limits of detection.

Advancing Mycotoxin Detection: Multivariate Rapid Analysis on Corn Using Surface Enhanced Raman Spectroscopy (SERS)

Mycotoxin contamination on food and feed can have deleterious effect on human and animal health. Agricultural crops may contain one or more mycotoxin compounds; therefore, a good multiplex detection method is desirable to ensure food safety. In this study, we developed a rapid method using label-free surface-enhanced Raman spectroscopy (SERS) to simultaneously detect three common types of mycotoxins found on corn, namely aflatoxin B1 (AFB1), zearalenone (ZEN), and ochratoxin A (OTA). The intrinsic chemical fingerprint from each mycotoxin was characterized by their unique Raman spectra, enabling clear discrimination between them. The limit of detection (LOD) of AFB1, ZEN, and OTA on corn were 10 ppb (32 nM), 20 ppb (64 nM), and 100 ppb (248 nM), respectively. Multivariate statistical analysis was used to predict concentrations of AFB1, ZEN, and OTA up to 1.5 ppm (4.8 µM) based on the SERS spectra of known concentrations, resulting in a correlation coefficient of 0.74, 0.89, and 0.72, respectively. The sampling time was less than 30 min per sample. The application of label-free SERS and multivariate analysis is a promising method for rapid and simultaneous detection of mycotoxins in corn and may be extended to other types of mycotoxins and crops.

High-efficiency SERS platform based on 3D porous PPDA@Au NPs as a substrate for the detection of pesticides on vegetables

Nowadays, the presence of highly toxic and persistent residues of pesticides in water and food around the world is becoming a serious problem, and so their rapid and sensitive detection is critical to human health. In this work, a 3D composite nanoparticle of porous PDA (polydopamine) microspheres and Au NPs (PPDA@Au NPs) was proposed as a SERS substrate to detect pesticides. Porous PDA as a substrate was first synthesized with F127 (Pluronic F127), dopamine hydrochloride, and 1,3,5-TMB (1,3,5-trimethylbenzene) under weakly alkaline conditions by a one-step method. Then, HAuCl4 was in situ reduced in the pores of PPDA spheres and grew sequentially for effecting the reducibility of PPDA. As a result, uniform 3D PPDA@Au NPs with "hot spots" were successfully synthesized as SERS substrates, which could effectively avoid the agglomeration of gold nanoparticles to greatly improve the sensitivity and uniformity of the SERS platform. At the same time, methyl parathion, 4-chlorophenol, and 2,4-D as representatives of pesticides were detected with the proposed PPDA@Au NP-based SERS platform, with detection limits lower than 7.26, 7.52, and 11 ng mL-1, separately. The current work presents a simple preparation method to prepare sensitive and uniform SERS platform PPDA@Au NPs, which have potential for applications in actual pesticide and drug testing.

A Fluorescent Molecularly Imprinted Polymer-Coated Paper Sensor for On-Site and Rapid Detection of Glyphosate

Due to the massive use and abuse of pesticides, practices which have led to serious threats to human health, the research community must develop on-site and rapid detection technology of pesticide residues to ensure food safety. Here, a paper-based fluorescent sensor, integrated with molecularly imprinted polymer (MIP) targeting glyphosate, was prepared by a surface-imprinting strategy. The MIP was synthesized by a catalyst-free imprinting polymerization technique and exhibited highly selective recognition capability for glyphosate. The MIP-coated paper sensor not only remained selective, but also displayed a limit of detection of 0.29 µmol and a linear detection range from 0.5 to 10 µmol. Moreover, the detection time only took about 5 min, which is beneficial for rapid detection of glyphosate in food samples. The detection accuracy of such paper sensor was good, with a spiked recovery rate of 92-117% in real samples. The fluorescent MIP-coated paper sensor not only has good specificity, which is helpful to reduce the food matrix interference and shorten the sample pretreatment time, but it also has the merits of high stability, low-cost and ease of operation and carrying, displaying great potential for application in the on-site and rapid detection of glyphosate for food safety.