Mesoporous silica supported orderly-spaced gold nanoparticles SERS-based sensor for pesticides detection in food

Unraveling the enhanced oxidative desulfurization activity: Synergistically boosting the formation of reactive oxygen species and active centers

Hydrogen peroxide (H2O2) activation is a pivotal factor influencing the oxidative desulfurization efficiency. Carbon quantum dots (C-dots) material can be facilely functionalized through chemical modifications, thus effectively activating H2O2 for oxidative reactions. Herein, a kind of hybrid materials C-dots-modified polyoxometalate poly(ionic liquid) supported on silica dioxide (C-PIL-POM-SiO2) were successfully synthesized via a facile self-assembly method. The experimental results demonstrated that the doped C-dots facilitated electron transfer during the reaction, thereby accelerating the conversion of H2O2 into superoxide (·O2-) and hydroxyl radicals (·OH). The incorporation of SiO2 significantly enhanced the specific surface area of the catalysts C-PIL-POM-SiO2, leading to abundant exposed active sites to boost the mass transfer during the reaction. The synergistic effects could achieve an optimal desulfurization efficiency of 99.9 % within 40 min.

Recent advances in the design of SERS substrates and sensing systems for (bio)sensing applications: Systems from single cell to single molecule detection

The Raman effect originates from spontaneous inelastic scattering of photons by matter. These photons provide a characteristic fingerprint of this matter, and are extensively utilized for chemical and biological sensing. The inherently lower generation of these Raman scattered photons, do not hold potential for their direct use in sensing applications. Surface enhanced Raman spectroscopy (SERS) overcomes the low sensitivity associated with Raman spectroscopy and assists the sensing of diverse analytes, including ions, small molecules, inorganics, organics, radionucleotides, and cells. Plasmonic nanoparticles exhibit localized surface plasmon resonance (LSPR) and when they are closely spaced, they create hotspots where the electromagnetic field is significantly enhanced. This amplifies the Raman signal and may offer up to a 10 14-fold SERS signal enhancement. The development of SERS active substrates requires further consideration and optimization of several critical features such as surface periodicity, hotspot density, mitigation of sample or surface autofluorescence, tuning of surface hydrophilicities, use of specific (bio) recognition elements with suitable linkers and bioconjugation chemistries, and use of appropriate optics to obtain relevant sensing outcomes in terms of sensitivity, cross-sensitivity, limit of detection, signal-to-noise ratio (SNR), stability, shelf-life, and disposability. This article comprehensively reviews the recent advancements on the use of disposable materials such as commercial grades of paper, textiles, glasses, polymers, and some specific substrates such as blue-ray digital versatile discs (DVDs) for use as SERS-active substrates for point-of-use (POU) sensing applications. The advancements in these technologies have been reviewed and critiqued for analyte detection in resource-limited settings, highlighting the prospects of applications ranging from single-molecule to single-cell detection. We conclude by highlighting the prospects and possible avenues for developing viable field deployable sensors holding immense potential in environmental monitoring, food safety and biomedical diagnostics.

Au nanoparticle-modified hollow carbon spheres as an advanced electrochemical sensing platform for effective detection of homocysteine in human serum

It is widely known that homocysteine (Hcy) is associated with the pathogenesis of many clinical diseases, and its quantitative detection can help early treatment of related diseases. The selection of materials with excellent properties is important for the construction of electrochemical sensing platforms and quantitative detection of Hcy. In this study, two nanocomposites, Au nanoparticles/hollow carbon spheres (AuNPs@HCS) and Au nanoparticles/solid carbon spheres (AuNPs@SCS), were prepared first. Then their morphology, structure and electrochemical behavior were investigated. And the comparison found that the HCSs have a large electroactive surface area and outstanding conductivity. Thanks to the catalytic properties of AuNPs and the synergistic effect of HCSs, AuNPs@HCS/GCE showed excellent electrochemical sensing performance for a wide range of Hcy concentrations with a detection limit down to 4.44 nM (S/N = 3). Moreover, the electrochemical mechanism of Hcy on Au@HCS/GCE is discussed in detail. Finally, in the actual serum sample assay, the sensor is used to detect Hcy directly and the recovery rate is satisfactory. This work may provide a valid method for the quantitative determination of Hcy in the future.

Recent advancements in the extraction and analysis of phthalate acid esters in food samples

Phthalate acid esters (PAEs) are ubiquitous environmental pollutants present in food samples, necessitating accurate detection for risk assessment and remediation efforts. This review provides an updated overview of the recent progress on the PAEs analysis regarding sample pretreatment techniques and analytical methodologies over the latest decade. Advances in sample preparation include solid-based extraction techniques replacing conventional liquid-liquid extraction, with solid sorbents emerging as promising alternatives due to their minimal solvent consumption and enhanced selectivity. Although techniques like the microextraction methods offer versatility and reduced solvent reliance, there is a need for more efficient and environmentally friendly techniques enabling on-site portable detection. High-resolution mass spectrometry is increasingly utilized for its enhanced sensitivity and reduced contamination risks. However, challenges persist in developing in situ analytical techniques for trace PAEs in complex food samples. Future research should prioritize novel analytical techniques with superior sensitivity and selectivity, addressing current limitations to meet the demand for precise PAEs detection in diverse food matrices.

Facile fabrication of Au-Ag alloy nanoparticles/Ag nanowires SERS substrates with bimetallic synergistic effect for ultra-sensitive detection of crystal violet and alkali blue 6B

The bimetallic nanostructure of Au and Ag can integrate two distinct properties into a novel substrate compared to single metal nanostructures. This work presents a rapid and sensitive surface-enhanced Raman scattering (SERS) substrate for detecting illegal food additives and dyes of crystal violet (CV) and alkali blue 6B (AB 6B). Au-Ag alloy nanoparticles/Ag nanowires (Au-Ag ANPs/Ag NWs) were prepared by solid-state ionics method and vacuum thermal evaporation method at 5μA direct current electric field (DCEF), the molar ratio of Au to Ag was 1:18.34. Many 40 nm-140 nm nanoparticles regularly existed on the surface of Ag NWs with the diameters from 80 nm to 150 nm. The fractal dimension of Au-Ag ANPs/Ag NWs is 1.69 due to macroscopic dendritic structures. Compared with single Ag NWs, the prepared Au-Ag ANPs/Ag NWs substrates show superior SERS performance because of higher surface roughness, the SERS active of Ag NWs and bimetallic synergistic effect caused by Au-Ag ANPs, so the limit of detections (LOD) of Au-Ag ANPs/Ag NWs SERS substrates toward detection of CV and AB 6B were as low as 10-16mol/L and 10-9mol/L, respectively. These results indicate that Au-Ag ANPs/Ag NWs substrates can be used for rapid and sensitive detection of CV and AB 6B and have great development potential for detection of illegal food additives and hazardous substances in the fields of environmental monitoring and food safety.

Rapid and simultaneous determination of mixed pesticide residues in apple using SERS coupled with multivariate analysis

This study aims to apply multivariate analysis algorithms for modeling the same spectra, for simultaneous determination of pymetrozine and carbendazim residues in apple. To mitigate the impact of competitive adsorption, SERS spectra are obtained from mixed solutions of pymetrozine and carbendazim at varying concentration ratios, which are then utilized for modeling. Results suggest that the PLSR model based on full-band SNV processed spectra shows the best performance for predicting pymetrozine and carbendazim contents, with R2 p of 0.9751 and 0.9779, RMSEP of 0.0492 and 0.5531 mg/L, RPD of 6.4297 and 6.8246, respectively. This model yielded R2 p of 0.9644 and 0.9671, RMSEP of 0.0747 and 0.8247 mg/L, RPD of 5.3857 and 5.6066 for pymetrozine and carbendazim in apple, respectively. The findings suggest that the proposed approach is suitable for simultaneous detection of pymetrozine and carbendazim in apples, offering a novel avenue for monitoring food safety.

A three-channel biosensor based on stimuli-responsive catalytic activity of the Fe3O4@Cu for on-site detection of tetrodotoxin in fish

Tetrodotoxin (TTX), a lethal neurotoxin, poses a grave threat to human health. The available spectroscopic methods suffer from limitations such as complex procedures and inadequate on-site capabilities. In this study, we proposed a method using Fe3O4@Cu as a catalytic biosensor combined with SERS, colorimetry and image processing for TTX detection. Integrating the aptamer amplifies the specificity of the system and masks the catalytic activity of Fe3O4@Cu. The catalytic efficiency of Fe3O4@Cu in the H2O2-TMB reaction can quantify the concentration of TTX in the system. Consequently, oxidation of TMB (oxTMB) led to the generation and change of signals for SERS, colorimetry and image processing, enabling a three-channel quantitative detection of TTX. Under the optimal conditions, the detection limit of established SERS, colorimetry and image processing were 0.055, 2.127 and 0.243 ng/mL, respectively. This three-channel biosensor was applied to real samples, providing an accurate, stable and adaptable alternative for on-site TTX detection.

Gold Nanoparticles: Multifunctional Properties, Synthesis, and Future Prospects

Gold nanoparticles (NPs) are among the most commonly employed metal NPs in biological applications, with distinctive physicochemical features. Their extraordinary optical properties, stemming from strong localized surface plasmon resonance (LSPR), contribute to the development of novel approaches in the areas of bioimaging, biosensing, and cancer research, especially for photothermal and photodynamic therapy. The ease of functionalization with various ligands provides a novel approach to the precise delivery of these molecules to targeted areas. Gold NPs' ability to transfer heat and electricity positions them as valuable materials for advancing thermal management and electronic systems. Moreover, their inherent characteristics, such as inertness, give rise to the synthesis of novel antibacterial and antioxidant agents as they provide a biocompatible and low-toxicity approach. Chemical and physical synthesis methods are utilized to produce gold NPs. The pursuit of more ecologically sustainable and economically viable large-scale technologies, such as environmentally benign biological processes referred to as green/biological synthesis, has garnered increasing interest among global researchers. Green synthesis methods are more favorable than other synthesis techniques as they minimize the necessity for hazardous chemicals in the reduction process due to their simplicity, cost-effectiveness, energy efficiency, and biocompatibility. This article discusses the importance of gold NPs, their optical, conductivity, antibacterial, antioxidant, and anticancer properties, synthesis methods, contemporary uses, and biosafety, emphasizing the need to understand toxicology principles and green commercialization strategies.

Reliable detection of malachite green by self-assembled SERS substrates based on gold-silicon heterogeneous nano pineapple structures

Morphology regulation of heterodimer nanoparticles and the use of their asymmetric features for further practical applications are crucial because of the rich optical properties and various combinations of heterodimers. This work used silicon to asymmetrically wrap half of a gold sphere and grew gold branches on the bare gold surface to form heterogeneous nano pineapples (NPPs) which can effectively improve Surface-enhanced Raman scattering (SERS) properties through chemical enhancement and lightning-rod effect respectively. The asymmetric structures of NPPs enabled them to self-assemble into the monolayer membrane with consistent branch orientation. The prepared substrate had high homogeneity and better SERS ability than disorganized substrates, and achieved reliable detection of malachite green (MG) in clams with a detection limit of 7.8 × 10-11 M. This work provided a guide to further revise the morphology of heterodimers and a new idea for the use of asymmetric dimers for practically photochemical and biomedical sensing.

Detection of Anthocyanins in Potatoes Using Micro-Hyperspectral Images Based on Convolutional Neural Networks

The color potato has the function of both a food and vegetable. The color potato not only contains various amino acids and trace elements needed by the human body but also contains anthocyanins. Anthocyanins have many functions, such as antioxidation, inflammation inhibition, vision improvement, and cancer prevention, so colored potatoes are deeply loved by consumers and have good market prospects. However, at present, the detection of anthocyanin content in color potatoes mainly depends on chemical methods, which are time-consuming and laborious, so it is necessary to study a fast and accurate detection method. In this study, microscopic hyperspectral equipment was used to collect the spectral information of the outer skin and inner skin of potatoes. The original spectrum, pretreatment spectrum, and characteristic spectrum variables of the outer skin and inner skin were predicted by the convolution neural network (CNN) algorithm and partial least squares regression (PLS) algorithm, respectively, and the performance of the model was evaluated by the prediction set correlation coefficient (Rp), prediction set root mean square error (RMSEP), correction set correlation coefficient (Rc), correction set root mean square error (RMSEC), and residual prediction deviation (RPD). The results revealed that the inner skin Raw + CNN model constructed under raw spectral data is optimal with Rc = 0.9508, RMSEC = 0.0374%, Rp = 0.9461, RMSEP = 0.2361% and RPD = 4.4933. The inner skin Savitzky-Golay (SG) + Detrend (DET) + CNN model constructed from pre-processed spectral data is optimal with Rc = 0.9499, RMSEC = 0.0359%, Rp = 0.9439, RMSEP = 0.2384%, RPD = 4.6516. The inner skin DET + competitive adaptive reweighted sampling (CARS) +CNN model constructed from the feature-based spectral data was optimal with Rc = 0.9527, RMSEC = 0.0708%, Rp = 0.9457, RMSEP = 0.2711%, and RPD = 4.1623. It can be seen that the Rp, RMSEP, Rc, RMSEC, and RPD values for modeling the spectral information of the inner skin were higher than those of the outer skin under the three different spectral data. The prediction accuracy of the model built by the CNN algorithm was better than the conventional algorithm PLS, the application of the CNN algorithm in inner skin can achieve accurate prediction of anthocyanin content in potato.

Plasmonic substrates for biochemical applications of surface-enhanced Raman spectroscopy

Due to its great practical importance, the detection and determination of many biomolecules in body fluids and other samples is carried out in a large number of laboratories around the world. One of the most promising analytical techniques now being widely introduced into medical analysis is surface-enhanced Raman scattering (SERS) spectroscopy. SERS is one of the most sensitive analytical methods, and in some cases, a good quality SERS spectrum dominated by the contribution of even a single molecule can be obtained. Highly sensitive SERS measurements can only be carried out on substrates generating a very high SERS enhancement factor and a low Raman spectral background, and so using of right nanomaterials is a key element in the success of SERS biochemical analysis. In this review article, we present progress that has been made in the preparation of nanomaterials used in SERS spectroscopy for detecting various kinds of biomolecules. We describe four groups of nanomaterials used in such measurements: nanoparticles of plasmonic metals and deposits of plasmonic nanoparticles on macroscopic substrates, nanocomposites containing plasmonic and non-plasmonic parts, nanostructured macroscopic plasmonic metals, and nanostructured macroscopic non-plasmonic materials covered by plasmonic films. We also describe selected SERS biochemical analyses that utilize the nanomaterials presented. We hope that this review will be useful for researchers starting work in this fascinating field of ​​science and technology.

Gold nanoparticle-based selective and efficient spectrophotometric assay for the insecticide methamidophos

A reliable, rapid, and inexpensive nano-sized chemosensor is presented for methamidophos (MET) - an insecticide. Poly(lactic acid) (PLA)-stabilized gold nanoparticles (AuNPs) were synthesized by a simple one-pot, two-phase chemical reduction method. The synthesized PLA-AuNPs were subsequently employed for selective, efficient, and quantitative detection of MET. MET is one of the highly toxic pesticides used for eradication of agricultural and urban insects. Upon the addition of MET, the wine-red color of PLA-AuNPs swiftly transformed into greyish-blue, further corroborated by a significant bathochromic and hyperchromic shift in the SPR band. The presence of other interfering insecticides, metal salts, and drugs did not have any pronounced effect on quantitative MET detection. The detection limit, the quantification limit, and linear dynamic range of MET utilizing PLA-AuNPs were  0.0027 µM, 0.005 µM, and 0.005-1000 µM, respectively. The PLA-AuNP-based assay renders an efficient, rapid, accurate, and selective quantification of MET in food, biological, and environmental samples. The proposed sensor provides an appropriate platform for fast and on-the-spot determination of MET without requiring a well-equipped lab setup.

Predicting wheat gluten concentrations in potato starch using GPR and SVM models built by terahertz time-domain spectroscopy

The purpose of this study was for the first time to explore the feasibility of terahertz (THz) spectral imaging for the detection of gluten contents in food samples. Based on the obtained 80 THz spectrum data, Gaussian process regression (GPR) and support vector machine (SVM) models were established to predict wheat gluten concentrations in 40 potato starch mixture samples. The prediction performances of GPR and SVM obtained were R2 = 0.859 and RMSE = 0.070, and R2 = 0.715 and RMSE = 0.101 in the gluten concentration range of 1.3%-100%, respectively, showing that the linear SVM algorithm had better prediction performance. The results indicated that THz spectral imaging combined with GPR could be used to predict the gluten content in food samples. It is thus hoped that this research should provide a novel technique for gluten content detection to ensure gluten-free food samples.

Breaking boundaries: Artificial intelligence for pesticide detection and eco-friendly degradation

Pesticides are extensively used agrochemicals across the world to control pest populations. However, irrational application of pesticides leads to contamination of various components of the environment, like air, soil, water, and vegetation, all of which build up significant levels of pesticide residues. Further, these environmental contaminants fuel objectionable human toxicity and impose a greater risk to the ecosystem. Therefore, search of methodologies having potential to detect and degrade pesticides in different environmental media is currently receiving profound global attention. Beyond the conventional approaches, Artificial Intelligence (AI) coupled with machine learning and artificial neural networks are rapidly growing branches of science that enable quick data analysis and precise detection of pesticides in various environmental components. Interestingly, nanoparticle (NP)-mediated detection and degradation of pesticides could be linked to AI algorithms to achieve superior performance. NP-based sensors stand out for their operational simplicity as well as their high sensitivity and low detection limits when compared to conventional, time-consuming spectrophotometric assays. NPs coated with fluorophores or conjugated with antibody or enzyme-anchored sensors can be used through Surface-Enhanced Raman Spectrometry, fluorescence, or chemiluminescence methodologies for selective and more precise detection of pesticides. Moreover, NPs assist in the photocatalytic breakdown of various organic and inorganic pesticides. Here, AI models are ideal means to identify, classify, characterize, and even predict the data of pesticides obtained through NP sensors. The present study aims to discuss the environmental contamination and negative impacts of pesticides on the ecosystem. The article also elaborates the AI and NP-assisted approaches for detecting and degrading a wide range of pesticide residues in various environmental and agrecultural sources including fruits and vegetables. Finally, the prevailing limitations and future goals of AI-NP-assisted techniques have also been dissected.

Surface-Enhanced Raman Spectroscopy Using a Silver Nanostar Substrate for Neonicotinoid Pesticides Detection

Surface-enhanced Raman spectroscopy (SERS) has been introduced to detect pesticides at low concentrations and in complex matrices to help developing countries monitor pesticides to keep their concentrations at safe levels in food and the environment. SERS is a surface-sensitive technique that enhances the Raman signal of molecules absorbed on metal nanostructure surfaces and provides vibrational information for sample identification and quantitation. In this work, we report the use of silver nanostars (AgNs) as SERS-active elements to detect four neonicotinoid pesticides (thiacloprid, imidacloprid, thiamethoxam and nitenpyram). The SERS substrates were prepared with multiple depositions of the nanostars using a self-assembly approach to give a dense coverage of the AgNs on a glass surface, which ultimately increased the availability of the spikes needed for SERS activity. The SERS substrates developed in this work show very high sensitivity and excellent reproducibility. Our research opens an avenue for the development of portable, field-based pesticide sensors, which will be critical for the effective monitoring of these important but potentially dangerous chemicals.

Identifying Surface-Enhanced Raman Spectra with a Raman Library Using Machine Learning

Since its discovery, surface-enhanced Raman spectroscopy (SERS) has shown outstanding promise of identifying trace amounts of unknown molecules in rapid, portable formats. However, the many different types of nanoparticles or nanostructured metallic SERS substrates created over the past few decades show substantial variability in the SERS spectra they provide. These inconsistencies have even raised speculation that substrate-specific SERS spectral libraries must be compiled for practical use of this type of spectroscopy. Here, we report a machine learning (ML) algorithm that can identify chemicals by matching their SERS spectra to those of a standard Raman spectral library. We use an approach analogous to facial recognition that utilizes feature extraction in the presence of multiple nuisance variables for spectral recognition. The key element is a metric we call "Characteristic Peak Similarity" (CaPSim) that focuses on the characteristic peaks in the SERS spectra. It has the flexibility to accommodate substrate-specific variability when quantifying the degree of similarity to a Raman spectrum. Analysis shows that CaPSim substantially outperforms existing spectral matching algorithms in terms of accuracy. This ML-based approach could greatly facilitate the spectroscopic identification of molecules in fieldable SERS applications.

Surface plasmon-assisted catalytic reduction of p-nitrothiophenol for the detection of Fe2+ by surface-enhanced Raman spectroscopy

Herein, we developed a concise, time-efficient, and high selective assay for detecting Fe2+ through its triggered surface plasmon-assisted reduction reaction of p-nitrothiophenol (PNTP) to p,p'-dimercaptoazobenzene (DMAB) on the surface of gold nanoparticles (AuNPs) based on surface-enhanced Raman scattering (SERS) spectroscopy. When Fe2+ was added to the PNTP-AuNPs system, the appearance of three characteristic peaks at 1142, 1392, and 1440 cm-1 attributed to DMAB demonstrated that Fe2+ induced the catalytic coupling reaction of PNTP. The Raman intensity ratio of the peak at 1142 cm-1 to the peak at 1336 cm-1 and the concentration of Fe2+ presented a good linear response from 10 to 100 μM with a limit of detection (LOD) of 0.35 μM. More importantly, the entire detection process can be completed within 2 min and further successfully used for the detection of Fe2+ in river water.

Advances in surface-enhanced Raman spectroscopy-based sensors for detection of various biomarkers

Surface enhanced Raman spectroscopy (SERS) allows the ultrasensitive detection of analytes present in traces or even single molecule levels by the generation of electromagnetic fields. It is a powerful vibrational spectroscopic method that is capable to detect traces of chemical and biological analytes. SERS technique is involved in the extremely sophisticated studies of molecules with high specificity and sensitivity. In the vicinity of nanomaterials decorated surfaces, SERS can monitor extremely low concentrations of analytes in a non-destructive manner with narrow line widths. This review article is focused on some recently developed SERS-based sensors for distinct types of analytes like disease-related biomarkers, organic and inorganic molecules, various toxins, dyes, pesticides, bacteria as well as single molecules. This study aims to enlighten the arising sensing approaches based on the SERS technique. Apart from this, some basics of the SERS technique like their mechanism, detection strategy, and involvement of some specific nanomaterials are also highlighted herein. Finally, the study concluded with some discussion of applications of SERS in various fields like food and environmental analysis.

A Novel Fluorescent Aptasensor Based on Mesoporous Silica Nanoparticles for Selective and Sensitive Detection of Saxitoxin in Shellfish

Background:

Saxitoxin (STX) stands as one of the most potent marine biotoxins, exhibiting high lethality. Despite its severity, current treatments remain ineffective, and existing detection techniques are limited due to ethical concerns and technical constraints.

Methods:

Herein, an innovative approach was constructed for STX detection, utilizing mesoporous silica nanoparticles (MSN) as a foundation. This innovative, easy, and label-free aptamer (Apt)- sensor was fabricated. Apts were employed as molecular identification probes and "gated molecules," while rhodamine 6G was encapsulated within particles to serve as a signal probe. In a lack of STX, Apts immobilized on an MSN surface kept a "gate" closed, preventing signal probe leakage. Upon the presence of STX, the "gate" opened, allowing a particular binding of Apts to STX and a subsequent release of a signal probe.

Results:

Experimental results demonstrated a positive correlation between fluorescence intensity and concentrations of STX within a range of 1 to 80 nM, with an exceptional limit of detection of 0.12 nM. Furthermore, the selectivity and stability of a biosensor were rigorously evaluated, validating its reliability.

Conclusion:

This newly developed sensing strategy exhibits remarkable performance in STX detection. Its success holds significant promise for advancing portable STX detection equipment, thereby addressing a pressing need for efficient and ethical detection methods in combating marine biotoxin contamination.

Silver decahedral nanoparticles with uniform and adjustable sizes for surface-enhanced Raman scattering-based thiram residue detection

Surface-enhanced Raman scattering (SERS) has been widely used as a sensitive molecular spectroscopy technology in food safety detection. Precise morphology control of plasmonic nanoparticles for high sensitivity and high uniformity SERS substrates remains challenging. Herein, silver decahedral nanoparticles (AgDeNPs) with uniform and adjustable sizes were synthesized by a photochemical seed-mediated method and utilized as SERS substrates for pesticide residue detection. The SERS sensitivity was demonstrated by using 4-mercaptobenzoic acid (4-MBA) as a typical model molecule, and the limit of detection (LOD) reached 1.0 × 10-13 M. The pesticide residue detection of thiram in aqueous solution and on fruit peels was successfully realized; the LODs were 1.0 × 10-11 M and 0.96 ng cm-2, respectively, and SERS repeatability was also proved. Overall, size-tunable AgDeNPs show attractive SERS performances and are expected to hold potential application in sensitive food and environmental safety detection.

A facile heat-treatment solid phase microextraction method for SERS detection of isocarbophos in tea using a hand-held Raman spectrometer

A facile sensor system based on heat-treatment solid phase microextraction and Surface-Enhanced Raman Scattering (HT-SPME-SERS) was established for in-situ detection of isocarbophos in complex tea matrix. Starting from the action optimization of temperature control unit and air flow control unit, pesticide molecules volatilizing from solution are efficiently captured by substrate and generate real-time SERS signals by a hand-held Raman spectrometer, and the sensor system based on HT-SPME-SERS was finally established. A novel SERS substrate of Cu@rGO@Ag was developed as HT-SPME-SERS material, where reduced graphene oxide (rGO) enriched pesticide molecules by π-π stacking. A superior detection sensitivity brought by the ultra-high enhancement effect of Cu@rGO@Ag substrate was obtained. A good linear relationship between Raman intensity and isocarbophos concentration was obtained and the limit of detection (LOD) was as low as 0.00451 ppm. The detection results obtained from the sensor system have been verified by gas chromatography-mass spectrometer (GC-MS), showing its great application potential for the safety of agricultural products.

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

Rapid identification and quantitative simultaneous analysis for multiple pesticide in real samples based on surface-enhanced Raman spectroscopy (SERS) is still a challenge because of sample complexity, reproducibility, and stability of SERS substrate. With use of colloidal silver nanoparticles loaded three-dimensional (3D) silica photonic microspheres (SPMs) array as the analytical platform, a SERS-based array assay for multiple pesticides was developed in this work. The silver nanoparticles were fixed into the gaps formed by the self-assembled nanospheres of the 3D SPMs to produce "hot spots", on which the Raman enhanced effect was up to 9.86 × 10⁷ and the maximum electric field enhancement effect reached to 9.75 times, ensuring the target pesticides on the surface of the SERS-substrate integrated SPM can be detected sensitively. Using 2,4-dichlorophenoxyacetic acid (2,4-D), glyphosate, and imidacloprid as the testing pesticides, the label-free and high-throughput SERS assay for simultaneous detection of the pesticides was established, giving good linear detection ranges (0.1-204.8 μg/mL for 2,4-D, 0.3-247.9 μg/mL for glyphosate, and 0.2-204.8 μg/mL for imidacloprid) and low detection limits (3.03 ng/mL for 2,4-D, 3.14 ng/mL for glyphosate, and 8.82 ng/mL for imidacloprid). The spiked recovery rates in the real samples were measured in the range of 82-112%, which was consistent with that of the classical standard methods. The label-free 3D SERS array analytical platform provides a powerful tool for high-throughput and low-cost screening of multiple pesticide residues in real samples.

Recent advances of Au@Ag core-shell SERS-based biosensors

The methodological advancements in surface-enhanced Raman scattering (SERS) technique with nanoscale materials based on noble metals, Au, Ag, and their bimetallic alloy Au-Ag, has enabled the highly efficient sensing of chemical and biological molecules at very low concentration values. By employing the innovative various type of Au, Ag nanoparticles and especially, high efficiency Au@Ag alloy nanomaterials as substrate in SERS based biosensors have revolutionized the detection of biological components including; proteins, antigens antibodies complex, circulating tumor cells, DNA, and RNA (miRNA), etc. This review is about SERS-based Au/Ag bimetallic biosensors and their Raman enhanced activity by focusing on different factors related to them. The emphasis of this research is to describe the recent developments in this field and conceptual advancements behind them. Furthermore, in this article we apex the understanding of impact by variation in basic features like effects of size, shape varying lengths, thickness of core-shell and their influence of large-scale magnitude and morphology. Moreover, the detailed information about recent biological applications based on these core-shell noble metals, importantly detection of receptor binding domain (RBD) protein of COVID-19 is provided.

Mesoporous silica coated core-shell nanoparticles substrate for size-selective SERS detection of chloramphenicol

With the growing popularity of the non-destructive technique, surface-enhanced Raman spectroscopy (SERS) demands a highly sensitive and reproducible plasmonic nanoparticles substrate. In this study, a novel bimetallic core-shell nanoparticles (Au@Ag@mSiO₂NP) substrate consisting of a gold core, silver shell, and a mesoporous silica coating was synthesized. The mesoporous coating structure was created by employing template molecules such as surfactant and their subsequent removal allowing selective screening based on the size of analyte molecules. Results showed that the plasmonic substrate could selectively enhance small molecules by preventing large macromolecules to reach the exciting zone of the substrate core, achieving the detection of chloramphenicol in milk samples with a detection limit of 6.68 × 10^-8 M. Moreover, the mesoporous coating provided additional stability to the Au@Ag nanoparticles, leading to the reusability of the substrate. Thus, this work offered a simple and smart Au@Ag@mSiO₂NP substrate for effective SERS detection of analytes.

Investigation of the adsorption of pymetrozine on the Au@AgNPs surface and its application in the rapid detection of pymetrozine residues in apple

Pymetrozine is widely used in agriculture to control pests, and its residue may pose a threat to humans. In this study, the adsorption behavior of pymetrozine on Au@AgNPs surfaces in different solutions was investigated by calculation of ACD/Labs, density functional theory, UV-vis spectra, zeta potential and surface-enhanced Raman scattering. Then, a SERS method for detection of pymetrozine residues in apples was established based on the adsorption study. The results showed that pymetrozine was adsorbed on Au@AgNPs surface in different forms in various solutions and high SERS sensitivity of pymetrozine was obtained by the synergistic effect of pymetrozine, Au@AgNPs and NaOH. A simple SERS method has been established to detect pymetrozine in apples with a LOD of 0.038 mg/kg, linear range of 0.05-1.00 mg/kg, recovery of 71.93-117.49 % and RSD low than 11.70 %. This study provides a reference for rapid detection of pymetrozine in agricultural products.

Fluorescent aptamer-modified mesoporous silica nanoparticles for quantitative acetamiprid detection

Acetamiprid (ACE) is widely used to control aphids, brown planthoppers, and other pests in agricultural production. However, ACE is difficult to degrade in the environment, resulting in excessive residue, which causes acute and chronic toxicity to human beings and non-target organisms. Therefore, the development of a rapid, convenient, and highly sensitive method to quantify ACE is essential. In this study, aminated mesoporous silica nanoparticles (MSNs-NH₂) were synthesized by one-pot method, and 6-carboxyl fluorescein modified aptamers (FAM-Apt) of ACE were adsorbed on the surface of MSNs-NH₂ by electrostatic interaction. Finally, a simple and sensitive fluorescence analysis method for the rapid detection of ACE was established. In the absence of ACE, the negatively charged FAM-Apt was electrostatically bound to the positively charged MSNs-NH₂, followed by centrifugation to precipitate MSNs-NH₂@FAM-Apt, and no fluorescent signal was detected in the supernatant. In the presence of ACE, the specific combination of FAM-Apt with ACE was greater than its electrostatic interaction with MSNs-NH₂, so that FAM-Apt was separated from MSNs-NH₂, and the supernatant had strong fluorescence signal after centrifugation. For ACE detection, the linear concentration range was 50-1100 ng/mL, and the detection limit (LOD) was 30.26 ng/mL. The method exhibited high sensitivity, selectivity and reproducibility, which is suitable for practical sample analysis and provides guidance for rapid detection of pesticide residues.

Fabrication and evaluation of chitosan modified filter paper for chlorpyrifos detection in wheat by surface-enhanced Raman spectroscopy

BACKGROUND

Chlorpyrifos is a commonly used organophosphorus pesticide in agriculture. However, its neurotoxicity poses a huge threat to human health. In the present study, a chitosan-modified filter paper-based surface enhanced Raman scattering active substrate (Ch/AgNPs/paper) was fabricated and used to detect trace amounts of chlorpyrifos in 120 treated wheat samples.

RESULTS

Results showed that the Ch/AgNPs/paper substrate could be used to enhance the chlorpyrifos spectral fingerprint only up to a concentration of 0.000558 mg L^-1 . Following Raman spectra acquisition, three pre-processing methods, including Savitzky-Golay (Savitsky-Golay filter with a second order polynomial) smoothing with first derivative and second derivative and normalization, were used to reduce baseline variation and increase resolutions of spectral peak features of the original spectra dataset. Then, prediction models based on partial least squares were established for detecting chlorpyrifos pesticide residue in wheat. The partial least squares model with normalization yielded optimal result, with a correlation coefficient of 0.9764, root mean square error of prediction of 1.22 mg L^-1 in the prediction, and relative analysis deviation of 4.12. Five unknown samples were prepared to verify the accuracy of the prediction model. The predicted recoveries were calculated to be between 97.25% and 119.38% with an absolute t value of 0.598. The value of a t-test shows that the prediction model is accurate and reliable.

CONCLUSION

The present study demonstrates that the proposed method can achieve rapid detection of chlorpyrifos in wheat. © 2022 Society of Chemical Industry.

3D Flexible SERS Substrates Integrated with a Portable Raman Analyzer and Wireless Communication for Point-of-Care Application

With the development of flexible surface-enhanced Raman spectroscopy (SERS) substrates that can realize rapid in situ detection, the SERS technique accompanied by miniaturized Raman spectrometers holds great promise for point-of-care testing (POCT). For an in situ detection strategy, constructing high-performance flexible and transparent SERS substrates through a facile and cost-effective fabrication method is critically important. Herein, we present a simple method for fabricating a large-area flexible and transparent SERS substrate consisting of a silver-nanoparticle-grafted wrinkled polydimethylsiloxane (Ag NPs@W-PDMS) film, using a surface-wrinkling technique and magnetron sputtering technology. By characterizing rhodamine 6G as a probe molecule with a portable Raman spectrometer, the flexible SERS substrate shows a low detection limit (10^-7 M), a high enhancement factor (6.11 × 10⁶), and excellent spot-spot and batch-batch reproducibilities (9.0% and 4.2%, respectively). Moreover, the Ag NPs@W-PDMS substrate maintains high SERS activity under bending and twisting mechanical deformations of over 100 cycles, as well as storage in air for 30 days. To evaluate its practical feasibility, in situ detection of malachite green on apple and tomato peels is performed with a detection limit of 10^-6 M. In addition, for point-of-care analysis, we develop a wireless transmission system to transmit the collected SERS spectral data to a computer in real time for signal processing and analysis. Therefore, the proposed Ag NPs@W-PDMS SERS substrate fabricated through a simple and mass-producible method, combined with the utilization of a portable Raman spectrometer and wireless communication, offers a promising opportunity to extend the SERS technique from the laboratory to POCT applications.

A scientometric study on application of electrochemical sensors for detection of pesticide using graphene-based electrode modifiers

Pesticide testing is an important topic in environmental protection and food safety. The development of green, accurate and reliable pesticide residue detection methods is an important technical support for implementing of agricultural quality supervision. Electrochemical sensors are a very promising analytical method for pesticide detection due to their high sensitivity, speed, low cost and portability. Performance enhancement of electrochemical sensors is often accompanied by research advances in materials science. Among them, carbon material is a very important electrode material for the fabrication of electrochemical sensors. The discovery of graphene makes it the most promising candidate among carbon materials for sensor performance enhancement. The topic of this review is the use of graphene-modified electrochemical sensors for pesticide detection in the last decade. Traditional literature summaries and bibliometric analyses were used for an in-depth analysis of this topic. In addition to the introduction of different sensor types and performance comparisons, this review also parses the authors' country, keywords and publication frequency. The related research experienced rapid growth several years ago and has now reached a relatively stable stage. We also discuss the perspectives on this topic.

Nanocomposite hydrogels for biomedical applications

Nanomaterials' unique structures at the nanometer level determine their incredible functions, and based on this, they can be widely used in the field of nanomedicine. However, nanomaterials do possess disadvantages that cannot be ignored, such as burst release, rapid elimination, and poor bioadhesion. Hydrogels are scaffolds with three-dimensional structures, and they exhibit good biocompatibility and drug release capacity. Hydrogels are also associated with disadvantages for biomedical applications such as poor anti-tumor capability, weak bioimaging capability, limited responsiveness, and so on. Incorporating nanomaterials into the 3D hydrogel network through physical or chemical covalent action may be an effective method to avoid their disadvantages. In nanocomposite hydrogel systems, multifunctional nanomaterials often work as the function core, giving the hydrogels a variety of properties (such as photo-thermal conversion, magnetothermal conversion, conductivity, targeting tumor, etc.). While, hydrogels can effectively improve the retention effect of nanomaterials and make the nanoparticles have good plasticity to adapt to various biomedical applications (such as various biosensors). Nanocomposite hydrogel systems have broad application prospects in biomedicine. In this review, we comprehensively summarize and discuss the most recent advances of nanomaterials composite hydrogels in biomedicine, including drug and cell delivery, cancer treatment, tissue regeneration, biosensing, and bioimaging, and we also briefly discussed the current situation of their commoditization in biomedicine.

Formation of Gold Nanoparticle Self-Assembling Films in Various Polymer Matrices for SERS Substrates

Surface-enhanced Raman spectroscopy (SERS) is regarded as a versatile tool for studying the composition and structure of matter. This work has studied the preparation of a SERS substrate based on a self-assembling plasmonic nanoparticle film (SPF) in a polymer matrix. Several synthesis parameters for the SPF are investigated, including the size of the particles making up the film and the concentration and type of the self-assembling agent. The result of testing systems with different characteristics is discussed using a model substance (pseudoisocyanin iodide). These models can be useful in the study of biology and chemistry. Research results contain the optimal parameters for SPF synthesis, maximizing the SERS signal. The optimal procedure for SPF assembly is determined and used for the synthesis of composite SPFs within different polymer matrices. SPF in a polymer matrix is necessary for the routine use of the SERS substrate for various types of analytes, including solid samples or those sensitive to contamination. Polystyrene, polyvinyl alcohol (PVA), and polyethylene are investigated to obtain a polymer matrix for SPF, and various methods of incorporating SPF into a polymer matrix are being explored. It is found that films with the best signal enhancement and reproducibility were obtained in polystyrene. The minimum detectable concentration for the SERS substrate obtained is equal to 10⁻¹⁰ M. We prepared a SERS substrate with an analytical enhancement factor of 2.7 × 10⁴, allowing an increase in the detection sensitivity of analyte solutions of five orders of magnitude.

Simultaneous determination of benzimidazole fungicides in food using signal optimized label-free HAu/Ag NS-SERS sensor

Extensively employed pesticide in agriculture causes residue in food products that would threaten public health safety. The surface-enhanced Raman scattering (SERS) signal reliant on double sensing of carbendazim and thiabendazole in a single step is achieved without the aid of any bio-recognition element. A label-free anisotropic bimetallic hollow Au/Ag nanostars (HAu/Ag NS) SERS substrate was synthesized with numerous hot spots for Raman molecule through a galvanic displacement-free deposition. The individual and mixed analyte calibration results were compared based on the identified peak at 1224 (carbendazim) and 778 (thiabendazole) cm^-1 and exhibited insignificant differences. The sensor could detect carbendazim and thiabendazole up to 4.28 × 10^-4 and 6.04 × 10^-4 µg·g^-1 or µg·mL^-1 in both individual and mixture of their extract. The recovery for accuracy and precision analysis was 91.54-98.26 % in rice and water. Finally, validation results were achieved satisfactorily (p > 0.05) with HPLC.

Recent advances in the application of Raman spectroscopy for fish quality and safety analysis

Fish is one of the highly demanded aquatic products, and its quality and safety play a pivotal role in daily diet. However, the possible hazardous substance in perishable fish both in pre- and postharvest periods may decrease their values and pose a threat to public health. Laborious and expensive traditional methods drive the need of developing effective tools for detecting fish quality and safety properties in a rapid, nondestructive, and effective manner. Recent advances in Raman spectroscopy (RS) and surface-enhanced Raman scattering (SERS) have shown enormous potential in various aspects, which largely boost their applications in fish quality and safety evaluation. They have incomparable merits such as providing molecule fingerprint information and allowing for rapid, sensitive, and noninvasive detection with simple sample preparation. This review provides a comprehensive overview focusing on the applications of RS and SERS for fish quality assessment and safety inspection, highlighting the hazardous substance and illegal behavior both in preharvest (veterinary drug residues and environmental pollutants) and postharvest (freshness and illegal behavior) particularly. Moreover, challenges and prospects are also proposed to facilitate the vigorous development of RS and SERS. This review is aimed to emphasize potential opportunities for applying RS and SERS as promising techniques for routine food quality and safety detection. PRACTICAL APPLICATION: With these applications, it can be clearly indicated that RS and SERS are promising and powerful in fish quality and safety surveillance, thereby reducing the occurrence of commercial fraud and food safety issues. More efforts still should be concentrated on exploiting the high-performance Raman instruments, establishing a universal Raman database, developing reproducible SERS substrates and combing RS with other versatile spectral techniques to promote these technologies from laboratory to practice. It is hoped that this review should arouse more research interests in RS and SERS technologies for fish quality and safety surveillance, as well as provide more insights to make a breakthrough.

Surface-Enhanced Raman Spectroscopy Substrates for Food Safety and Quality Analysis

Surface-enhanced Raman spectroscopy (SERS) has been identified as a fundamental surface-sensitive technique that boosts Raman scattering by adsorbing target molecules on specific surfaces. The application of SERS highly relies on the development of smart SERS substrates, and thus the fabrication of SERS substrates has been constantly improved. Herein, we investigate the impacts of different substrates on SERS technology including plasmonic metal nanoparticles, semiconductors, and hybrid systems in quantitative food safety and quality analysis. We first discuss the fundamentals, substrate designs, and applications of SERS. We then provide a critical review of the recent progress of SERS in its usage for screening and detecting chemical and biological contaminants including fungicides, herbicides, insecticides, hazardous colorants, and biohazards in food samples to assess the analytical capabilities of this technology. Finally, we investigate the future trends and provide practical techniques that could be used to fulfill the requirements for rapid analysis of food at a low cost.

Rapid Determination of Mixed Pesticide Residues on Apple Surfaces by Surface-Enhanced Raman Spectroscopy

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.

Large-area and low-cost SERS substrates based on a gold-coated nanostructured surface fabricated on a wafer-scale

This paper demonstrates a method to fabricate plasmonic nanostructures over a large area that can be implemented as SERS substrates. The proposed method comprises batch processes such as spin coating, reactive ion etching, and thin metal deposition. These processes can be performed on large wafers, resulting in large numbers of SERS substrates in a single run. The effects of different process parameters were studied to optimize the performance of the SERS substrates. The study of sensitivity on the optimized SERS substrates was conducted using the SERS-active molecule pMBA. The SERS substrates thus fabricated were able to detect molecule concentrations as low as 100 nM. The SERS substrates were also evaluated for uniformity across the sample and for sample-to-sample reproducibility. Finally, the SERS substrates were applied to demonstrate label-free detection of organophosphorous pesticides - paraoxon ethyl and paraoxon methyl.

A REVIEW ON DETERMINATION OF THE VETERINARY DRUG RESIDUES IN FOOD PRODUCTS

In this paper, we discuss veterinary medicine and its applications in the food field as well as its risk to the health of humans and animals by the residues. We review how the veterinary residues enter and cause some detrimental effects. We also mention two techniques to determine the residue of veterinary medication that existed in food originating from animals, including classic and advanced techniques. Finally, we discuss the potential of various developed methods compared to some traditional techniques.

The characteristics of Raman spectroscopy of isomer CBD- and THC-Au nanoparticles using the density functional theory

The isomers cannabidiol (CBD) and Δ9-tetrahydrocannabinol (THC) can both be extracted from cannabis. We use density functional theory to study the Raman activity spectra, frontier molecular orbitals, and molecular electrostatic potentials of CBD, THC, and their respective gold complexes. A "selectivity enhancement" phenomenon for the spectral peaks at frequencies of 1144 cm^-1 and 1553 cm^-1 in the Raman spectrum of the CBD-Au_n complex, and at frequencies of 865 cm^-1, 1335 cm^-1, and 1553 cm^-1 in the Raman spectrum of the THC-Au_n complex, was observed and explained. The frontier molecular orbital energy gaps of CBD and THC are 5.4085 eV and 5.4461 eV, respectively, indicating that CBD is more likely to react than THC. The CBD/THC-Au complexes had the strongest chemical activities and greater charge transfer effects with an Au₃ cluster. The most electronegative sites of CBD and THC were found from molecular electrostatic potential (MEP) mapping. It is assumed that these sites are the adsorption sites of the CBD/THC molecules and gold surface. The MEP of the CBD/THC complexes also demonstrates the charge transfer effect between CBD/THC and Au. Both the "selectivity" phenomenon in the Raman activity spectra of the complex and the above assumption are explained by a surface selection rule. The conformation of the CBD/THC molecules on the gold surface are determined, showing that CBD is adsorbed vertically through the resorcinol structure while THC is adsorbed vertically through the tetrahydropyran and benzene ring.

Development of a Rapid Gold Nanoparticle Immunochromatographic Strip Based on the Nanobody for Detecting 2,4-DichloRophenoxyacetic Acid

2,4-Dichlorophenoxyacetic acid (2,4-D) is a systemic conductive herbicide widely used across the world. With the large-scale and continuous use of 2,4-D, its possible harm to the environment and non-target organisms has attracted increasing attention, and the construction of a stable rapid on-site detection method is particularly important. In order to achieve on-site rapid detection of 2,4-D, we developed a gold nanoparticle immunochromatographic strip method with the visual elimination value was 50 ng/mL, and a quantitative detection limit of 11 ng/mL based on a nanobody. By combing with the color snap, the immunochromatographic strip could quantitatively analyze the amounts of 2,4-D. Meanwhile, a colorimetric card based on the true color of the test strips was developed for the qualitative analysis of 2,4-D on-site. The samples (water, fruits and vegetables) with and without 2,4-D were detected by the immunochromatographic strips, and the results showed the accuracy and reliability. Thus, this assay is a rapid and simple on-site analytical tool to detect and quantify 2,4-D levels in environmental samples, and the analytical results can be obtained in about ten minutes. In addition, the nanobody technology used in this study provides an inexhaustible supply of a relatively stable antibodies that can be archived as a nanobody, plasmid or even its sequence.

Development of Au NPs-decorated filter paper as a SERS platform for the detection of benzidine

In this paper, a simple and cost-efficient strategy was used to construct a uniform Au NPs distribution on the surface of flexible filter paper for the detection of benzidine. Taking full advantage of the adsorption properties of filter paper, small gold nanoparticles were adsorbed onto its surface as gold seeds, and subsequently grown by electroless plating to form a highly uniform distribution of Au NPs substrates. By changing the electroless plating time, an optimal substrate was obtained. The as-prepared substrate exhibited satisfactory sensitivity with a low detection limit of 10-13 M for 4-ATP, and good reproducibility and homogeneity. Furthermore, the as-prepared substrates were successfully used for the detection of benzidine in environmental water, with a minimum detection concentration as low as 0.1 ppm and recoveries in the range of 92.4 to ∼108.5%. This study indicated that filter paper-based SERS substrates have great potential value in the detection of environmental organic pollutants.

Surface Enhanced Raman Spectroscopy: Applications in Agriculture and Food Safety

Recent global warming has resulted in shifting of weather patterns and led to intensification of natural disasters and upsurges in pests and diseases. As a result, global food systems are under pressure and need adjustments to meet the change—often by pesticides. Unfortunately, such agrochemicals are harmful for humans and the environment, and consequently need to be monitored. Traditional detection methods currently used are time consuming in terms of sample preparation, are high cost, and devices are typically not portable. Recently, Surface Enhanced Raman Scattering (SERS) has emerged as an attractive candidate for rapid, high sensitivity and high selectivity detection of contaminants relevant to the food industry and environmental monitoring. In this review, the principles of SERS as well as recent SERS substrate fabrication methods are first discussed. Following this, their development and applications for agrifood safety is reviewed, with focus on detection of dye molecules, melamine in food products, and the detection of different classes of pesticides such as organophosphate and neonicotinoids.

Rapid field trace detection of pesticide residue in food based on surface-enhanced Raman spectroscopy

Surface-enhanced Raman spectroscopy is an alternative detection tool for monitoring food security. However, there is still a lack of a conclusion of SERS detection with respect to pesticides and real sample analysis, and the summary of intelligent algorithms in SERS is also a blank. In this review, a comprehensive report of pesticides detection using SERS technology is given. The SERS detection characteristics of different types of pesticides and the influence of substrate on inspection are discussed and compared by the typical ways of classification. The key points, including the progress in real sample analysis and Raman data processing methods with intelligent algorithm, are highlighted. Lastly, major challenges and future research trends of SERS analysis of pesticide residue are also addressed. SERS has been proven to be a powerful technique for rapid test of residue pesticides in complex food matrices, but there still is a tremendous development space for future research.

A Sensitive SERS Method for Determination of Pymetrozine in Apple and Cabbage Based on an Easily Prepared Substrate

Residual pesticides are one of the major food safety concerns around the world. There is a demand for simple and reliable methods to monitor pesticide residues in foods. In this study, a sensitive method for determination of pymetrozine in apple and cabbage samples using surface-enhanced Raman spectroscopy (SERS) based on decanethiol functionalized silver nanoparticles was established. The proposed method performed satisfactorily with the linear detection range of 0.01-1.00 mg/L and limit of detection (LOD) of 0.01 mg/L in methanol. In addition, it was successfully used to detect pymetrozine in apple and cabbage samples, the LOD was 0.02 and 0.03 mg/L, respectively, and the recoveries of spiked cabbage and apple ranged 70.40-104.00%, with relative standard deviations below 12.18% and 10.33% for intra-day and inter-day tests. Moreover, the results of the correlation test with real cabbage samples of liquid chromatography-tandem mass spectrometry showed that they were highly correlated (slope = 0.9895, R2 = 0.9953). This study provides a sensitive approach for detection of pymetrozine in apple and cabbage, which has great potential for determination of pymetrozine residues in food products.

Ultrasensitive fluorescence immunosensor based on mesoporous silica and magnetic nanoparticles: Capture and release strategy

Herein we designed a novel, highly sensitive, simple and amplified fluorescence immunosensing strategy for hepatitis B virus surface antigen (HBV surface antigen) (HBsAg) as a model based on the construction of a sandwich type probe. The operation mechanism of this immunosensing strategy is implemented by capturing and then stimulation-based-releasing of entrapped dye in the fluorescent capsules. The proposed probe is made by the Fe₃O₄ magnetic nanoparticle (Fe₃O₄ MNP) as a probe collector site and the Rhodamine B loaded-mesoporous silica nanoparticle (MSN-Rh.B) as a fluorescent mesoporous capsule and signal amplifier site. Such a methodology is benefited, from the advantages of the high ability of MSNs to be used as a scaffold for efficient dye encapsulation and the magnetic nanoparticles as efficient biological carriers. Under optimal conditions, the fluorescence signal (The fluorescence of solutions was measured using a quartz fluorescence cell (PMT voltage:720, Ex wavelegth:540, Em wavelength:568, All measurements were carried out at room temperature) increased with the increment of HBsAg concentration in the linear dynamic range of 6.1 ag/ml to 0.012 ng/ml with a detection limit (LOD) of 5.7 ag/ml. The relative standard deviation, measured between the resulting fluorescence peaks was obtained by 6.0%.