Review of surface enhanced Raman spectroscopic (SERS) detection of synthetic chemical pesticides

A review on nanomaterial-based SERS substrates for sustainable agriculture

The agricultural sector plays a pivotal role in driving the economy of many developing countries. Any dent in this economical structure may have a severe impact on a country's population. With rising climate change and increasing pollution, the agricultural sector is experiencing significant damage. Over time this cumulative damage will affect the integrity of food crops and create food security issues around the world. Therefore, an early warning system is needed to detect possible stress on food crops. Here we present a review of the recent developments in nanomaterial-based Surface Enhanced Raman Spectroscopy (SERS) substrates which could be utilized to monitor agricultural crop responses to natural and anthropogenic stress. Initially, our review delves into diverse and cost-effective strategies for fabricating SERS substrates, emphasizing their intelligent utilization across various agricultural scenarios. In the second phase of our review, we spotlight the specific application of SERS in addressing critical food security issues. By detecting nutrients, hormones, and effector molecules in plants, SERS provides valuable insights into plant health. Furthermore, our exploration extends to the detection of contaminants, chemicals, and foodborne pathogens within plants, showcasing the versatility of SERS in ensuring food safety. The cumulative knowledge derived from these discussions illustrates the transformative potential of SERS in bolstering the agricultural economy. By enhancing precision in nutrient management, monitoring plant health, and enabling rapid detection of harmful substances, SERS emerges as a pivotal tool in promoting sustainable and secure agricultural practices. Its integration into agricultural processes not only augments productivity but also establishes a robust defence against potential threats to crop yield and food quality. As SERS continues to evolve, its role in shaping the future of agriculture becomes increasingly pronounced, promising a paradigm shift in how we approach and address challenges in food production and safety.

Rapid and ultrasensitive detection of thiram and carbaryl pesticide residues in fruit juices using SERS coupled with the chemometrics technique

A gold nanogap substrate was used to measure the thiram and carbaryl residues in various fruit juices using surface-enhanced Raman scattering (SERS). The gold nanogap substrates can detect carbaryl and thiram with limits of detection of 0.13 ppb (0.13 μgkg-1) and 0.22 ppb (0.22 μgkg-1). Raw SERS data were first preprocessed to reduce noise and undesirable effects and, were later used for model creation, implementing classification, and regression analysis techniques. The partial least-squares regression models achieved the highest prediction correlation coefficient (R2) of 0.99 and the lowest root mean square of prediction value below 0.62 ppb for both pesticide-infected juice samples. Furthermore, to differentiate between juice samples contaminated by both pesticides and control (pesticide-free), logistic-regression classification models were produced and achieved the highest classification accuracies of 100% and 99% for contaminated juice containing thiram and 100% accurate results for contaminated juice containing carbaryl. This indicates that the gold nanogap surface has significant potential for achieving high sensitivity in detecting trace contaminants in food samples.

In situ study of the interactions between metal surfaces and cationic surfactant corrosion inhibitors by surface-enhanced Raman spectroscopy coupled with visible spectroscopy

Cationic surfactants are widely used as corrosion inhibitors for industrial tubings and pipelines. They protect the surface of steel pipes through a film-forming mechanism, providing both anodic and cathodic inhibition. To improve the efficiency of the corrosion protection, it is essential to understand the interactions between the surfactants and metal surfaces. To achieve this, surface enhanced Raman spectroscopy (SERS) can serve as a powerful tool due to its surface sensitivity and potential to detect trace amounts of analytes in complex media. In this contribution, we have investigated the behaviour of in situ prepared AgNPs in the presence of benzalkonium chloride as a model corrosion inhibitor using SERS coupled to visible spectroscopy and combined with light scattering methods. By combining these experimental methods, we were able to correlate the aggregation of silver particles with the concentration of added surfactant in the resulting mixture. Using this insight, we also established a SERS method for the detection of benzalkonium chloride traces in water. For this, we utilised the quenching of the SERS response of methylene blue by competitive adsorption of methylene blue and the surfactant on SERS active AgNPs. We believe that our approach can serve a variety of applications to improve the industrial water treatment. For example, the modelling of the interaction of different surfactants with SERS can be used for process intensification, and ultimately, to move towards the digital twinning of corrosion processes for more efficient corrosion inhibition. Furthermore, the ability to adapt our sensing protocol for on-line corrosion inhibitor monitoring allows a fast response to process changes, hence, enabling resource-efficient, continuous process control.

Surface segregation of rigid polyarylene ether amidoxime on polyurethane nanofiber into hierarchical membranes as substrate of flexible SERS nanosensor for sulfamethoxazole detection

Electrospun polymeric nanofibrous membranes are emerging as the promising substrates for preparation of flexible SERS nanosensors due to their intrinsic nanoscale surface roughness, easy scalability as well as rich surface reactivity. Although the nanofiber membranes prepared from high performance thermoplastics exhibit good mechanical stability, the SERS nanosensors based on these substrates normally have lower signal-to-noise ratio because of the interference from background Raman signals of aromatic moieties. Herein, we synthesized an optically transparent polyurethane (PU) and rigid polyarylene ether amidoxime (PEA), which were electrospun into core-shell nanofibers membranes with a "beads-on-web" morphology. Furthermore, the PU-PEA membranes were coated with ultra-thin silver layer and thermally annealed to prepare the flexible SERS nanosensor without any background noises. In addition, the Raman enhancement of SERS nanosensor can be readily improved by tuning of PU-PEA composition, silver thickness as well as thermal annealing temperature. Finally, the optimized SERS nanosensor enables label-free detection of sulfamethoxazole as low as 0.1 nM with a good reproducibility and detection performance in real water sample. Meanwhile, the optimized SERS nanosensor shows long term anti-biofouling capacity. Thanks to its facile fabrication, competitive analytical performance and resistance to biofouling, the current work basically open new way for design of flexible SERS nanosensors for biomedical applications.

Deep learning-based Raman spectroscopy qualitative analysis algorithm: A convolutional neural network and transformer approach

Raman spectroscopy is a general and non-destructive detection technique that can obtain detailed information of the chemical structure of materials. In the past, when using chemometric algorithms to analyze the Raman spectra of mixtures, the challenges of complex spectral overlap and noise often limited the accurate identification of components. The emergence of deep learning has introduced a novel approach to qualitative analysis of mixed Raman spectra. In this paper, we propose a deep learning-based Raman spectroscopy qualitative analysis algorithm (RST) by borrowing the ideas of convolutional neural network and Transformer. By transforming the Raman spectrum into 64 word vectors, the contribution weights of each word vector to the components are obtained. For the 75 spectral data used for validation, the positive identification rate can reach 100.00 %, the recall rate can reach 99.3 %, the average identification score can reach 9.51, and it is applicable to the fields of Raman and surface-enhanced Raman spectroscopy. Furthermore, compared with traditional CNN models, RST has excellent accuracy and robustness in identifying components in complex mixtures. The model's interpretability has been enhanced, aiding in a deeper understanding of spectroscopic learning patterns for future analysis of more complex mixtures.

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.

Thermophoresis-Induced Polymer-Driven Destabilization of Gold Nanoparticles for Optically Directed Assembly at Interfaces

The limitations of conventional template-based methods for the deposition of nanoparticle assemblies into defined patterns on solid substrates call for the development of techniques that do not require templates or lithographic masks. The use of optically-induced thermal gradients to drive the migration of colloids toward or away from a laser spot, known as opto-thermophoresis, has shown promise for the low-power trapping and optical manipulation of a variety of colloidal species. However, the printing of colloids using this technique has so far not been established. Herein, a method for the optically directed printing of noble metal nanoparticles, specifically gold nanospheres is reported. The thermophoresis of the polymer polyvinylpyrrolidone and gold nanospheres toward a laser spot led to the deposition of nanoparticle aggregates, capable of serving as surface-enhanced Raman scattering substrates. The influence of heating laser power and the concentrations of polymer, salt, and surfactant on the nanoparticle deposition rate and structure of the printed pattern are studied, showing that a variety of conditions can permit printing, suggesting facile generalization to different nanoparticle compositions, sizes, and shapes. These findings will greatly benefit future efforts for directed nanoparticle assembly, and drive applications in sensing, photothermal heating, and relevant applications in biomedicine and devices.

Surface-Enhanced Raman Spectroscopy and Electrochemistry: The Ultimate Chemical Sensing and Manipulation Combination

One of the lessons we learned from the COVID-19 pandemic is that the need for ultrasensitive detection systems is now more critical than ever. While sensors' sensitivity, portability, selectivity, and low cost are crucial, new ways to couple synergistic methods enable the highest performance levels. This review article critically discusses the synergetic combinations of optical and electrochemical methods. We also discuss three key application fields-energy, biomedicine, and environment. Finally, we selected the most promising approaches and examples, the open challenges in sensing, and ways to overcome them. We expect this work to set a clear reference for developing and understanding strategies, pros and cons of different combinations of electrochemical and optical sensors integrated into a single device.

Microbiological and chemical hazards in cultured meat and methods for their detection

Cultured meat, which involves growing meat in a laboratory rather than breeding animals, offers potential benefits in terms of sustainability, health, and animal welfare compared to conventional meat production. However, the cultured meat production process involves several stages, each with potential hazards requiring careful monitoring and control. Microbial contamination risks exist in the initial cell collection from source animals and the surrounding environment. During cell proliferation, hazards may include chemical residues from media components such as antibiotics and growth factors, as well as microbial issues from improper bioreactor sterilization. In the differentiation stage where cells become muscle tissue, potential hazards include residues from scaffolding materials, microcarriers, and media components. Final maturation and harvesting stages risk environmental contamination from nonsterile conditions, equipment, or worker handling if proper aseptic conditions are not maintained. This review examines the key microbiological and chemical hazards that must be monitored and controlled during the manufacturing process for cultured meats. It describes some conventional and emerging novel techniques that could be applied for the detection of microbial and chemical hazards in cultured meat. The review also outlines the current evolving regulatory landscape around cultured meat and explains how thorough detection and characterization of microbiological and chemical hazards through advanced analytical techniques can provide crucial data to help develop robust, evidence-based food safety regulations specifically tailored for the cultured meat industry. Implementing new digital food safety methods is recommended for further research on the sensitive and effective detection of microbiological and chemical hazards in cultured meat.

All-in-One Electrokinetic Strategy Coupled with a Miniaturized Chip for SERS Detection of Multipesticides

Complexed and tiresome pretreatment processes have significantly impeded in-field analysis of environmental specimens. Herein, an all-in-one sample separation and enrichment strategy based on a compact charge-selective capture/nanoconfined enrichment (CSC/NCE) device is exploited for marker-free surface-enhanced Raman spectroscopy (SERS) detection of charged pesticides in matrix specimens. This tactic incorporating in situ separations, seizing, and nanoconfined enhancement can greatly elevate the effectiveness of sample pretreatment. Importantly, CSC/NCE with excellent adsorption performances and excellent plasmonic features facilitates concentration and signal amplification of electrically charged pesticides. With the introduction of an electric field on this integrated CSC/NCE, the matrix effect in samples could be significantly eradicated, and a distinct SERS response is witnessed for targeted analytes. Accurate quantification of multipesticides is achieved by synergizing the CSC/NCE chip and chemometrics, and the contents found by the CSC/NCE-based sensing strategy agree with those obtained from chromatography assays with relative deviations lower than 10%. The facile and versatile all-in-one tactic infused in a compact chip exhibits enormous potential for field-test application in chemical measurement and food safety.

Rapid and specific detection of thiabendazole: enzymatic digestion-enabled fluorescent aptasensor

Thiabendazole, a widely used broad-spectrum fungicide in agriculture, poses risks to human health. To monitor its presence in water, we propose a fluorescent aptasensor utilizing Escherichia coli exonuclease I (Exo I). The findings demonstrate a linear correlation between thiabendazole concentrations and digestion percentage, with a detection limit (LOD) exceeding 1 µM and a determination coefficient (R2) of 0.959. This aptamer-based fluorescence spectroscopy detection system holds promise for a rapid, specific, and sensitive analysis of thiabendazole in environmental waters and food matrices.

Pesticide Identification Using Surface-Enhanced Raman Spectroscopy and Density Functional Theory Calculations: From Structural Insights to On-Site Detection

Pesticides play an important role in conventional agriculture. Yet, their harmful effects on the environment are becoming increasingly apparent. The occurrence of pesticides is hence being monitored worldwide. For fast, easy, yet sensitive identification, surface-enhanced Raman spectroscopy (SERS) is a powerful tool. In this study, a method is introduced that may be amended to in-field detection of pesticides. Gold and silver nanoparticles were synthesized, size-tailored, and characterized. The herbicide paraquat and the fungicide thiram served as model compounds. The preparation yielded reproducible SERS spectra. Using quantum chemical computation, Raman and SERS spectra were calculated and analyzed. The interpretation of vibrational modes in combination with SERS enhancement and attenuation allowed us to identify compound-specific bands. The assignment was interpreted in terms of the orientation of paraquat and thiram on the gold and silver nanoparticle surfaces. Paraquat preferred a co-planar arrangement parallel to the gold nanoparticle surface and a head-on orientation on the silver nanoparticle. For thiram, breaking of the disulfide bond was recognized, such that interaction with the surface occurred via the sulfur atoms. Successful detection of the pesticides after recollection from vegetable leaves demonstrated the method's applicability for pesticide identification.

RamanSPy: An Open-Source Python Package for Integrative Raman Spectroscopy Data Analysis

Raman spectroscopy is a nondestructive and label-free chemical analysis technique, which plays a key role in the analysis and discovery cycle of various branches of science. Nonetheless, progress in Raman spectroscopic analysis is still impeded by the lack of software, methodological and data standardization, and the ensuing fragmentation and lack of reproducibility of analysis workflows thereof. To address these issues, we introduce RamanSPy, an open-source Python package for Raman spectroscopic research and analysis. RamanSPy provides a comprehensive library of tools for spectroscopic analysis that supports day-to-day tasks, integrative analyses, the development of methods and protocols, and the integration of advanced data analytics. RamanSPy is modular and open source, not tied to a particular technology or data format, and can be readily interfaced with the burgeoning ecosystem for data science, statistical analysis, and machine learning in Python. RamanSPy is hosted at https://github.com/barahona-research-group/RamanSPy, supplemented with extended online documentation, available at https://ramanspy.readthedocs.io, that includes tutorials, example applications, and details about the real-world research applications presented in this paper.

Integrated surface-enhanced Raman spectroscopy and convolutional neural network for quantitative and qualitative analysis of pesticide residues on pericarp

Pesticide residue poses a significant global public health concern, necessitating improved detection methods. Here, a novel platform was introduced based on surface-enhanced Raman spectroscopy (SERS) to detect ten distinct types of pesticides. Notably, the sensitivity of this approach is exemplified by detecting trace amounts of 50 pM (10 ppt) thiabendazole. The correlation between the characteristic peak intensity of coexisting pesticides and their concentrations displays an exceptional linear relationship (R2 = 0.9999), underscoring its utility for quantitative mixed pesticide detection. Additionally, qualitative analysis of five mixed pesticides was conducted leveraging distinctive peak labeling. Harnessing machine learning techniques, a model for classifying and predicting pesticides on pericarps was developed. Remarkably, the convolutional neural network achieved classification accuracy of 100 % and prediction accuracy of 99.62 %. This innovative approach accurately identifies and quantifies diverse pesticides, thus offering a feasible scheme for in-situ detection of pesticide residues. Ultimately, this strategy contributes to ensuring food safety and public health.

Highly sensitive detection of tryptophan based on Schiff base reaction and surface-enhanced Raman spectroscopy

In this study, a simple, rapid and sensitive method combining surface-enhanced Raman spectroscopy and Schiff base reaction was developed for the detection of tryptophan. This method does not require product separation to obtain a significant Raman signal of the derivatized product, and the derivatization reaction can be controlled by experimental parameters such as reaction temperature, time, concentration of derivatization reagent and concentration of sodium nitrite. The characteristic peak of the derivative of tryptophan (1620 cm-1) was selected for quantitative analysis, and the intensity of the characteristic Raman spectrum peak showed a linear relationship with the concentration of tryptophan (10-8-10-4 mol/L) in the range of with a correlation coefficient R2 of 0.9922. This assay combines surface-enhanced Raman spectroscopy and Schiff base reaction, which is characterized by high sensitivity and easy operation, and has good application prospects in the detection of tryptophan in food.

A stable and sensitive 2D SERS sensor for bioanalytical applications

In this study, we describe a 2D-SERS sensor obtained by deposition of spherical gold nanoparticles (AuNPs) onto a suitably functionalized metal surface. Morphological analysis of the SERS surface by SEM and AFM demonstrated a uniform and stable distribution of the active nanoparticles. Following p-mercaptoaniline (pMA) functionalization, the sensor was characterized by co-localized Raman measurements, demonstrating a significant enhancement in Raman signals with homogeneous SERS activity across the entire sampled area. The as-prepared SERS sensor was demonstrated to be suitable for Therapeutic Drug Monitoring (TDM) of 6-mercaptopurine (6-MP), exhibiting a linear correlation between analyte concentration and SERS intensity in the range 5 - 20 μM. This work highlights the potential of 2D-SERS sensors for hypersensitive and accurate analytical measurements, particularly in the biomedical field.

Intelligent Rapid Detection Techniques for Low-Content Components in Fruits and Vegetables: A Comprehensive Review

Fruits and vegetables are an important part of our daily diet and contain low-content components that are crucial for our health. Detecting these components accurately is of paramount significance. However, traditional detection methods face challenges such as complex sample processing, slow detection speed, and the need for highly skilled operators. These limitations fail to meet the growing demand for intelligent and rapid detection of low-content components in fruits and vegetables. In recent years, significant progress has been made in intelligent rapid detection technology, particularly in detecting high-content components in fruits and vegetables. However, the accurate detection of low-content components remains a challenge and has gained considerable attention in current research. This review paper aims to explore and analyze several intelligent rapid detection techniques that have been extensively studied for this purpose. These techniques include near-infrared spectroscopy, Raman spectroscopy, laser-induced breakdown spectroscopy, and terahertz spectroscopy, among others. This paper provides detailed reports and analyses of the application of these methods in detecting low-content components. Furthermore, it offers a prospective exploration of their future development in this field. The goal is to contribute to the enhancement and widespread adoption of technology for detecting low-content components in fruits and vegetables. It is expected that this review will serve as a valuable reference for researchers and practitioners in this area.

High-performance, large-area flexible SERS substrates prepared by reactive ion etching for molecular detection

In the realm of molecular detection, the surface-enhanced Raman scattering (SERS) technique has garnered increasing attention due to its rapid detection, high sensitivity, and non-destructive characteristics. However, conventional rigid SERS substrates are either costly to fabricate and challenging to prepare over a large area, or they exhibit poor uniformity and repeatability, making them unsuitable for inspecting curved object surfaces. In this work, we present a flexible SERS substrate with high sensitivity as well as good uniformity and repeatability. First, the flexible polydimethylsiloxane (PDMS) substrate is manually formulated and cured. SiO2/Ag layer on the substrate can be obtained in a single process by using ion beam sputtering. Then, reactive ion etching is used to etch the upper SiO2layer of the film, which directly leads to the desired densely packed nanostructure. Finally, a layer of precious metal is deposited on the densely packed nanostructure by thermal evaporation. In our proposed system, the densely packed nanostructure obtained by etching the SiO2layer directly determines the SERS ability of the substrate. The bottom layer of silver mirror can reflect the penetrative incident light, the spacer layer of SiO2and the top layer of silver thin film can further localize the light in the system, which can realize the excellent absorption of Raman laser light, thus enhancing SERS ability. In the tests, the prepared substrates show excellent SERS performance in detecting crystalline violet with a detection limit of 10-11M. The development of this SERS substrate is anticipated to offer a highly effective and convenient method for molecular substance detection.

Deep Learning Enabled SERS Identification of Gaseous Molecules on Flexible Plasmonic MOF Nanowire Films

Through the capture of a target molecule at the metal surface with a highly confined electromagnetic field induced by surface plasmon, surface enhanced Raman spectroscopy (SERS) emerges as a spectral analysis technology with high sensitivity. However, accurate SERS identification of a gaseous molecule with low density and high velocity is still a challenge due to its difficulty in capture. In this work, a flexible paper-based plasmonic metal-organic framework (MOF) film consisting of Ag nanowires@ZIF-8 (AgNWs@ZIF-8) is fabricated for SERS detection of gaseous molecules. Benefiting from its micronanopores generated by the nanowire network and ZIF-8 shell, the effective capture of the gaseous molecule is achieved, and its SERS spectrum is obtained in this paper-based flexible plasmonic MOF nanowire film. With optimal structure parameters, spectra of gaseous 4-aminothiophenol, 4-mercaptophenol, and dithiohydroquinone demonstrate that this film has good SERS performance, which could maintain obvious Raman signals within 30 days during reproducible detection. To realize SERS identification of gaseous molecules, deep learning is performed based on the SERS spectra of the mixed gaseous analyte obtained in this flexible porous film. The results point out that an artificial neural network algorithm could identify gaseous aldehydes (gaseous biomarker of colorectal cancer) in simulated exhaled breath with high accuracy at 93.7%. The integration of the flexible paper-based film sensors with deep learning offers a promising new approach for noninvasive colorectal cancer screening. Our work explores SERS applications in gaseous analyte detection and has broad potential in clinical medicine, food safety, environmental monitoring, etc.

Recombinant Organophosphorus acid anhydrolase (OPAA) enzyme-carbon quantum dot (CQDs)-immobilized thin film biosensors for the specific detection of Ethyl Paraoxon and Methyl Parathion in water resources

Organophosphates pesticide (OP) toxicity through water resources is a large concern globally among all the emerging pollutants. Detection of OPs is a challenge which needs to be addressed considering the hazardous effects on the health of human beings. In the current research thin film biosensors of recombinant, Organophosphorus acid anhydrolase (OPAA) enzyme along with carbon quantum dots (CQDs) immobilized in thin films were developed. OPAA-CQDs thin film biosensors were used for the specific detection of two OPs Ethyl Paraoxon (EP) and Methyl Parathion (MP) in river water and household water supply. Recombinant OPAA enzyme was expressed in E. Coli, purified and immobilized on the CQD containing chitosan thin films. The CQDs used for this purpose were developed by a one-pot hydrothermal method from phthalic acid and Tri ethylene diamine. The properties of CQDs, OPAA and thin films were characterized using techniques like XPS, TEM, XRD, enzyme activity and CLSM measurements. Biosensing studies of EP and MP were performed by taking fluorescence measurements using a fiber optic spectrometer. The analytical parameters of biosensing were compared against an estimation carried out using the HPLC method. The biosensing performance indicates that the OPAA-CQDs thin film-based biosensors were able to detect both EP and MP in a range of 0-100 μM having a detection limit of 0.18 ppm/0.69 ppm for EP/MP, respectively with a response time of 5 min. The accuracy of estimation of EP/MP when spiked in water resources lie in the range of ∼100-102% which clearly indicates the OPAA-CQD based thin film biosensors can function as a point-of-use method for the detection of OP pesticides in complex water resources.

One-step fabrication of flexible polyamide@Ag-dodecanethiol membranes for highly sensitive SERS detection of thiram

The surface-enhanced Raman scattering (SERS) is an effective spectral technology based on Raman scattering, but in practice, the commonly used SERS substrates suffer from low sensitivity and poor stability. In order to overcome these limitations, the SERS substrates were prepared from hydrophobic modification of dodecanethiol (C12) coupled with a flexible substrate, which was then used for pesticides detection in water. A flexible PA@Ag-C12 substrate with surface functionalization has been obtained. This work aims to investigate the self-assembly of Ag NPs modified with C12 onto polyamide (PA) membranes. Initially, transmission electron microscopy and scanning electron microscopy were used to analyze the substrate's morphology. Then with the help of an energy-dispersive spectrometer, sulfur content of C12-modified Ag NPs was analyzed. In order to determine the hydrophobicity of the modified Ag NPs, the contact angle was used. The results indicate that the gap between Ag NPs on PA membrane can be effectively controlled in order to prevent Ag NPs from aggregating. Furthermore, the finite-difference time-domain analysis indicated that the PA@Ag-C12 substrate exhibited a stronger electromagnetic enhancement effect than the PA@Ag substrate. By reducing NPs gaps on the PA membrane, the number of 'hot spots' increased, and the SERS performance of the substrate was improved as a result. According to the results of this study, this method can greatly reduce the manufacturing costs and time costs of the SERS substrate while maintaining the original uniformity. The SERS performance of PA@Ag-C12 was found to be three orders of magnitude better than that of PA@Ag direct self-assembled substrate, and the detection limit for Rhodamine 6G (R6G) was approximately 8.47 × 10-14M. On the basis of the PA@Ag-C12 substrate, thiram is detectable at a detection limit of 5.88 × 10-11M with a high degree of sensitivity and repeatability.

Recent Development and Applications of Stretchable SERS Substrates

Surface-enhanced Raman scattering (SERS) is a cutting-edge technique for highly sensitive analysis of chemicals and molecules. Traditional SERS-active nanostructures are constructed on rigid substrates where the nanogaps providing hot-spots of Raman signals are fixed, and sample loading is unsatisfactory due to the unconformable attachment of substrates on irregular sample surfaces. A flexible SERS substrate enables conformable sample loading and, thus, highly sensitive Raman detection but still with limited detection capabilities. Stretchable SERS substrates with flexible sample loading structures and controllable hot-spot size provide a new strategy for improving the sample loading efficiency and SERS detection sensitivity. This review summarizes and discusses recent development and applications of the newly conceptual stretchable SERS substrates. A roadmap of the development of SERS substrates is reviewed, and fabrication techniques of stretchable SERS substrates are summarized, followed by an exhibition of the applications of these stretchable SERS substrates. Finally, challenges and perspectives of the stretchable SERS substrates are presented. This review provides an overview of the development of SERS substrates and sheds light on the design, fabrication, and application of stretchable SERS systems.

Preparation of arsenic(III) monoclonal antibodies and preliminary evaluation of a novel silver-coated gold nanorod SERS immunoassay strip construction

Heavy metal pollution has become a growing concern in industrial, agricultural, and manufacturing processes, posing a significant threat to human health. Among these heavy metals, arsenic (As) is highly toxic and shares similar chemical properties and environmental behavior with other heavy metals. As(III) is particularly toxic compared to other forms of arsenic. Therefore, it is essential to develop a real-time, rapid, and sensitive method for the determination of As(III). In this study, we employed a unique bifunctional chelator, 1-(4-isothiocyanobenzyl)-ethylenediamine N,N,N',N'-tetraacetic acid (ITCBE), to prepare a complete antigen. Through a series of tests including balb/c mouse immunization, cell fusion (mouse L2041 spleen cells with mouse myeloma cells SP2/0), and subcloning, we generated four monoclonal cell lines (1C1, 2C2, 3A9, and 4A11). These cell lines demonstrated high purity, high affinity, and IC50 values of less than 50 μg mL-1. Monoclonal antibody 4A11, which exhibited a strong Raman signal, was selected as the probe, and Au@Ag 200 was utilized as the surface-enhanced Raman scattering (SERS) substrate for the preliminary establishment of SERS immunochromatographic test strips. The sensitivity of the SERS immunochromatographic test strips, measured through Raman signal detection, showed a significant improvement compared to the SERS immunochromatographic test strips analyzed by colorimetry (LOD = 49.43 μg mL-1 and LDR = 5.32-81.31 μg mL-1). The SERS immunochromatographic test strips achieved a LOD of 7.62 μg mL-1 and an LDR of 12.66-71.84 μg mL-1. This study presents innovative methodologies for the rapid detection of As(III) using SERS immunochromatographic test strips.

Ultrasensitive detection of crystal violet using a molybdenum sulfide-silver nanostructure-based sensing platform: roles of the adsorbing semiconductor in SERS signal enhancement

Crystal violet (CV) is an organic dye that is stabilized by the extensive resonance delocalization of electrons over three electron-donating amine groups. This prevents the molecule from being linked to a metal surface, and therefore, reduces the sensitivity of surface-enhanced Raman scattering (SERS) sensors for this toxic dye. In this work, we improved the sensing performance of a silver-based SERS sensor for CV detection by modifying the active substrate. Molybdenum sulfide (MoS2) nanosheets were employed as a scaffold for anchoring electrochemically synthesized silver nanoparticles (e-AgNPs) through a single step of ultrasonication, leading to the formation of MoS2/Ag nanocomposites. As an excellent adsorbent, MoS2 promoted the adsorption of CV onto the surface of the substrate, allowing more CV molecules to be able to experience the SERS effect originating from the e-AgNPs. Hence, the SERS signal of CV was significantly enhanced. In addition, the effects of the MoS2 content of the nanocomposites on their SERS performance were also taken into account. Using MoS2/Ag with the most optimal MoS2 content of 10%, the SERS sensor exhibited the best enhancement of the SERS signal of CV with an impressive detection limit of 1.17 × 10-11 M in standard water and 10-9 M in tap water thanks to an enhancement factor of 2.9 × 106, which was 11.2 times higher than that using pure e-AgNPs.

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.

Pesticide biosensors: trends and progresses

Pesticides, chemical substances extensively employed in agriculture to optimize crop yields, pose potential risks to human and environmental health. Consequently, regulatory frameworks are in place to restrict pesticide residue concentrations in water intended for human consumption. These regulations are implemented to safeguard consumer safety and mitigate any adverse effects on the environment and public health. Although gas chromatography- and liquid chromatography-mass spectrometry (GC-MS and LC-MS) are highly efficient techniques for pesticide quantification, their use is not suitable for real-time monitoring due to the need for sophisticated laboratory pretreatment of samples prior to analysis. Since they would enable analyte detection with selectivity and sensitivity without sample pretreatment, biosensors appear as a promising alternative. These consist of a bioreceptor allowing for specific recognition of the target and of a detection platform, which translates the biological interaction into a measurable signal. As early detection systems remain urgently needed to promptly alert and act in case of pollution, we review here the biosensors described in the literature for pesticide detection to advance their development for use in the field.

Glyphosate-Exonuclease Interactions: Reduced Enzymatic Activity as a Route to Glyphosate Biosensing

N-phosphonomethyle-glycine (glyphosate) is the most widely used pesticide worldwide due to its effectiveness in killing weeds at a moderate cost, bringing significant economic benefits. However, owing to its massive use, glyphosate and its residues contaminate surface waters. On site, fast monitoring of contamination is therefore urgently needed to alert local authorities and raise population awareness. Here the hindrance of the activity of two enzymes, the exonuclease I (Exo I) and the T5 exonuclease (T5 Exo) by glyphosate, is reported. These two enzymes digest oligonucleotides into shorter sequences, down to single nucleotides. The presence of glyphosate in the reaction medium hampers the activity of both enzymes, slowing down enzymatic digestion. It is shown by fluorescence spectroscopy that the inhibition of ExoI enzymatic activity is specific to glyphosate, paving the way for the development of a biosensor to detect this pollutant in drinking water at suitable detection limits, i.e., 0.6 nm.

Construction of a SERS platform for sensitive detection of aflatoxin B1 based on CRISPR strategy

Aflatoxin B1, a pathogen in the aflatoxin family, has attracted much attention due to the harmfulness in production and life. However, the common methods like high performance liquid chromatography used for detection of AFB1 have deficiency in complicated pretreatment processes, and the purification effect is not ideal. Herein, a SERS platform based on CRISPR strategy was designed for sensitive detection of AFB1. By synthesizing core-shell nanoparticles embedded with Raman silent region dye molecules, Prussian blue (PB), the detection of the sensor reduced background interference and the SERS signal was calibrated. At the same time, the high-efficiency reverse cleavage activity of cas12a was used to convert non-nucleic acid targets into nucleic acid, so as to achieve the effect of sensitive detection of AFB1 with a detection limit of 3.55  pg/mL. This study provides a new thought for SERS detection of non-nucleic acid targets in the future.

Advances in Microfluidics Techniques for Rapid Detection of Pesticide Residues in Food

Food safety is a significant issue that affects people worldwide and is tied to their lives and health. The issue of pesticide residues in food is just one of many issues related to food safety, which leave residues in crops and are transferred through the food chain to human consumption. Foods contaminated with pesticide residues pose a serious risk to human health, including carcinogenicity, neurotoxicity, and endocrine disruption. Although traditional methods, including gas chromatography, high-performance liquid chromatography, chromatography, and mass spectrometry, can be used to achieve a quantitative analysis of pesticide residues, the disadvantages of these techniques, such as being time-consuming and costly and requiring specialist staff, limit their application. Therefore, there is a need to develop rapid, effective, and sensitive equipment for the quantitative analysis of pesticide residues in food. Microfluidics is rapidly emerging in a number of fields due to its outstanding strengths. This paper summarizes the application of microfluidic techniques to pyrethroid, carbamate, organochlorine, and organophosphate pesticides, as well as to commercial products. Meanwhile, the study also outlines the development of microfluidics in combination with 3D printing technology and nanomaterials for detecting pesticide residues in food.

Optimization of silver nanoparticles synthesis by chemical reduction to enhance SERS quantitative performances: Early characterization using the quality by design approach

Surface-enhanced Raman scattering (SERS) is a vibrational widely used technique thanks to its multiple advantages such as its high specificity and sensitivity. The Raman signal exaltation comes from the use of metallic nanoparticles (Nps) acting as antennas by amplifying the Raman scattering. Controlling the Nps synthesis is a major point for the implementation of SERS in routine analysis and especially in quantitative applications. Effectively, nature, size and shape of these Nps considerably influence the SERS response intensity and repeatability. The Lee-Meisel protocol is the most common synthesis route used by the SERS community due to the low cost, rapidity and ease of manufacturing. However, this process leads to a significant heterogeneity in terms of particle size and shape. In this context, this study aimed to synthesize repeatable and homogeneous silver nanoparticles (AgNps) by chemical reduction. The Quality by Design strategy from quality target product profile to early characterization design was considered to optimize this reaction. The first step of this strategy aimed to highlight critical parameters by the means of an early characterization design. Based on an Ishikawa diagram, five process parameters were studied: the reaction volume as categorical variable and the temperature, the time of reaction, the trisodium citrate concentration and pH as continuous variables. A D-Optimal design of 35 conditions was performed. Three critical quality attributes were selected to maximize the SERS intensity, minimize the variation coefficient on SERS intensities and the polydispersity index of the AgNps. Considering these factors, it appeared that concentration, pH and time of reaction were identified as having a critical impact on the Nps formation and can then be considered for the further optimization step.

Porous silicon decorated with Au/TiO2 nanocomposites for efficient photoinduced enhanced Raman spectroscopy

In this study, we investigated the potential of porous silicon (PSi) modified with Au/TiO₂ nanocomposites (NCPs) as a substrate for photoinduced enhanced Raman spectroscopy (PIERS). One-step pulsed laser-induced photolysis (PLIP) was used to embed Au/TiO₂ NCPs in the surface of PSi. Scanning electron microscopy revealed that adding TiO₂ nanoparticles (NPs) during PLIP led to the formation of predominantly spherical Au NPs with a diameter of approximately 20 nm. Furthermore, modifying the PSi substrate with Au/TiO₂ NCPs considerably enhanced the Raman signal of rhodamine 6G (R6G) after 4 h of ultraviolet (UV) irradiation. Real-time monitoring of the Raman signals of R6G at different concentrations under UV irradiation revealed that the amplitude of the signals increased with the irradiation time for R6G concentrations ranging from 10^-3 M to 10^-5 M. PSi substrates decorated with Au/TiO₂ NCPs may be used to develop materials for PIERS applications.

Highly sensitive technique for detection of adulterants in centella herbal samples using surface enhanced Raman spectroscopy (SERS)

The trace level detection of adulterants in food, nutritional supplements and medicinal herbs is highly challenging in the field of food processing and herbal industries. In addition, laborious sample processing procedures and well trained personnel are required to analyse the samples using conventional analytical equipments. In this study, a highly sensitive technique with minimal sampling processes and human intervention is proposed for the trace amount detection of pesticidal residues in centella powder. Herein, graphene oxide gold (GO-Au) nanocomposite coated parafilm is developed as substrate by simple dropcasting technique to facilitate dual surface enhanced Raman signal. The dual SERS enhancement involving chemical enhancement from graphene and electromagnetic signal enhancement from gold nanoparticles is utilized for detection of chlorpyrifos in the ppm level concentration. The flexible polymeric surfaces could be the better choice for SERS substrates due to their inherent properties such as flexibility, transparency, roughness and hydrophobicity. Among the various types of flexible substrates explored, GO-Au nanocomposites coated parafilm substrates showed better Raman signal enhancement. Parafilm coated with GO-Au nanocomposites is successful in achieving detection limits down to 0.1 ppm of chlorpyrifos in centella herbal powder sample. Thus, the fabricated parafilm based GO-Au SERS substrates could be used as a screening tool at quality control of herbal product manufacturing sectors for trace level detection of adulterants in herbal samples from their unique chemical and structural information.

Screening for pesticide residues in cocoa (Theobroma cacao L.) by portable infrared spectroscopy

Rapid assessment of pesticide residues ensures cocoa bean quality and marketability. In this study, a portable FTIR instrument equipped with a triple reflection attenuated total reflectance (ATR) accessory was used to screen cocoa beans for pesticide residues. Cocoa beans (n = 75) were obtained from major cocoa growing regions of Peru and were quantified for pesticides by gas chromatography (GC) or liquid chromatography (LC) coupled with mass spectrometry (MS). The FTIR spectra were used to detect the presence of pesticides in cocoa beans or lipid fraction (butter) by using a pattern recognition (Soft Independent Modeling by Class Analogy, SIMCA) algorithm, which produced a significant discrimination for cocoa nibs (free or with pesticides). The variables related to the class grouping were assigned to the aliphatic (3200-2800 cm^-1) region with an interclass distance (ICD) of 3.3. Subsequently, the concentration of pesticides in cocoa beans was predicted using a partial least squares regression analysis (PLSR), using an internal validation of the PLRS model, the cross-validation correlation coefficient (R_val = 0.954) and the cross-validation standard error (SECV = 14.9 mg/kg) were obtained. Additionally, an external validation was performed, obtaining the prediction correlation coefficient (R_pre = 0.940) and the standard error of prediction (SEP = 16.0 μg/kg) with high statistical performances, which demonstrates the excellent predictability of the PLSR model in a similar real application. The developed FTIR method presented limits of detection and quantification (LOD = 9.8 μg/kg; LOQ = 23.1 μg/kg) with four optimum factors (PC). Mid-infrared spectroscopy (MIR) offered a viable alternative for field screening of cocoa.

UV-Nanoimprint Lithography for Predefined SERS Nanopatterns Which Are Reproducible at Low Cost and High Throughput

A controlled and reliable nanostructured metallic substrate is a prerequisite for developing effective surface-enhanced Raman scattering (SERS) spectroscopy techniques. In this study, we present a novel SERS platform fabricated using ultra-violet nanoimprint lithography (UV-NIL) to produce large-area, ordered nanostructured arrays. By using UV-NIL imprinted patterns in resist, we were able to overcome the main limitations present in most common SERS platforms, such as nonuniformity, nonreproducibility, low throughput, and high cost. We simulated and fabricated C-shaped plasmonic nanostructures that exhibit high signal enhancement at an excitation wavelength of 785 nm. The substrates were fabricated by directly coating the imprinted resist with a thin gold layer. Avoiding the need to etch patterns in silicon significantly reduces the time and cost of fabrication and facilitates reproducibility. The functionality of the substrates for SERS detection was validated by measuring the SERS spectra of Rhodamine 6G.

Recent development of surface-enhanced Raman scattering for biosensing

Surface-Enhanced Raman Scattering (SERS) technology, as a powerful tool to identify molecular species by collecting molecular spectral signals at the single-molecule level, has achieved substantial progresses in the fields of environmental science, medical diagnosis, food safety, and biological analysis. As deepening research is delved into SERS sensing, more and more high-performance or multifunctional SERS substrate materials emerge, which are expected to push Raman sensing into more application fields. Especially in the field of biological analysis, intrinsic and extrinsic SERS sensing schemes have been widely used and explored due to their fast, sensitive and reliable advantages. Herein, recent developments of SERS substrates and their applications in biomolecular detection (SARS-CoV-2 virus, tumor etc.), biological imaging and pesticide detection are summarized. The SERS concepts (including its basic theory and sensing mechanism) and the important strategies (extending from nanomaterials with tunable shapes and nanostructures to surface bio-functionalization by modifying affinity groups or specific biomolecules) for improving SERS biosensing performance are comprehensively discussed. For data analysis and identification, the applications of machine learning methods and software acquisition sources in SERS biosensing and diagnosing are discussed in detail. In conclusion, the challenges and perspectives of SERS biosensing in the future are presented.

Improved charge-transfer resonance in graphene oxide/ZrO2 substrates for plasmonic-free SERS determination of methyl parathion

This work reports a sensitive SERS substrate based on graphene oxide (GO) and quantum-sized ZrO₂ nanoparticles (GO/ZrO₂) for label-free determination of the organophosphate pesticide methyl parathion (MP). The enhanced light-matter interactions and the consequent SERS effect in these substrates resulted from the effective charge transfer (CT) mechanism attributed to synergistic contributions of three main factors: i) the strong molecular adherence of the MP molecules and the ZrO₂ surface which allows the first layer-effect, ii) the relatively abundant surface defects in low dimensional ZrO₂ semiconductor NPs, which act as intermediate electronic states that reduce the large bandgap barrier, and iii) the hindered charge recombination derived from the transference of the photoinduced holes to the GO layer. This mechanism allowed an enhancement factor of 8.78 × 10⁴ for GO/ZrO₂-based substrates, which is more than 5-fold higher than the enhancement observed for platforms without GO. A detection limit of 0.12 μM was achieved with an outstanding repeatability (variation ≤4.5%) and a linear range up to 10 μM, which is sensitive enough to determine the maximal MP concentration permissible in drinking water according to international regulations. Furthermore, recovery rates between 97.4 and 102.1% were determined in irrigation water runoffs, strawberry and black tea extracts, demonstrating the reliability of the hybrid GO/ZrO₂ substrate for the organophosphate pesticides quantification in samples related to agri-food sectors and environmental monitoring.

Luminescent Guests Encapsulated in Metal-Organic Frameworks for Portable Fluorescence Sensor and Visual Detection Applications: A Review

Metal-organic frameworks (MOFs) have excellent applicability in several fields and have significant structural advantages, due to their open pore structure, high porosity, large specific surface area, and easily modifiable and functionalized porous surface. In addition, a variety of luminescent guest (LG) species can be encapsulated in the pores of MOFs, giving MOFs a broader luminescent capability. The applications of a variety of LG@MOF sensors, constructed by doping MOFs with LGs such as lanthanide ions, carbon quantum dots, luminescent complexes, organic dyes, and metal nanoclusters, for fluorescence detection of various target analyses such as ions, biomarkers, pesticides, and preservatives are systematically introduced in this review. The development of these sensors for portable visual fluorescence sensing applications is then covered. Finally, the challenges that these sectors currently face, as well as the potential for future growth, are briefly discussed.

An accuracy improved ratiometric SERS sensor for rhodamine 6G in chili powder using a metal-organic framework support

Internal standard molecule 4-mercaptobenzoic acid (4-MBA) embedded Au core-Ag shell nanorods (Au-MBA@Ag NRs) were prepared by a seed-mediated growth method, then loaded on octahedral MIL-88B-NH₂ to obtain a novel ratiometric SERS substrate of Au-MBA@Ag NRs/PSS/MIL-88B-NH₂ (AMAPM) for detecting rhodamine 6G (R6G) in chili powder. The porous structure and excellent adsorption ability of MIL-88B-NH₂, allowed for increased loading of Au-MBA@Ag NRs, thereby shortening the distance between adsorbed R6G and the "hot spot" resulting from local surface plasmon resonance (LSPR) of Au-MBA@Ag NRs. Based on the SERS characteristic peak ratio of R6G to 4-MBA, the ratiometric SERS substrate displayed improved accuracy and excellent performance for R6G detection, with a wide linear range of 5-320 nM and a low detection limit of 2.29 nM as well as fine stability, reproducibility and specificity. The proposed ratiometric SERS substrate offered a simple, fast and sensitive sensing strategy for R6G detection in chili powder, which demonstrated potential applications in food safety and the analysis of trace analytes in complex matrices.

Current electroanalytical approaches in the carbamates and dithiocarbamates determination

Pesticides are a suitable tool for controlling plagues and disease vectors. However, their inappropriate use allows for contamination of the environment, soil, water, and foods. Carbamates and dithiocarbamates pesticides present accumulative effects in the human body resulting in hormonal, neurological and reproductive disorders, and some are still suspected or proven to give carcinogenic or mutagenic effects. This review provides a current electroanalytical approach in the carbamates and dithiocarbamates determination, showing the use of voltammetric techniques such as amperometry, cyclic and linear scan, differential pulse, and square wave voltammetry, indicating their advantages, disadvantages, and perspectives in electroanalytical detection of carbamates and dithiocarbamates in natural water and foods. Also are reported the different materials used in the preparation of working electrodes since their choice has an important impact on the success of the analytical applications, resulting in suitable sensitivity, selectivity, stability, and robustness.

Nondestructive testing methods for pesticide residue in food commodities: A review

Pesticides play an important role in increasing the overall yield and productivity of agricultural foods by controlling pests, insects, and numerous plant-related diseases. However, the overuse of pesticides has resulted in pesticide contamination of food products and water bodies, as well as disruption of ecological and environmental systems. Global health authorities have set limits for pesticide residues in individual food products to ensure the availability of safe foods in the supply system and to assist farmers in developing the best agronomic practices for crop production. Therefore, the use of nondestructive testing (NDT) methods for pesticide residue detection is gaining interest in the food supply chain. The NDT techniques have several advantages, such as simultaneous measurement of chemical and physical characteristics of food without destroying the product. Although numerous studies have been conducted on NDT for pesticide residue in agro-food products, there are still challenges in real-time implementation. Further study on NDT methods is needed to establish their potential for supplementing existing methods, identifying mixed pesticides, and performing volumetric quantification (not surface accumulation alone).

Iodine-Modified Ag NPs for Highly Sensitive SERS Detection of Deltamethrin Residues on Surfaces

It is essential to estimate the indoor pesticides/insecticides exposure risk since reports show that 80% of human exposure to pesticides occurs indoors. As one of the three major contamination sources, surface collected pesticides contributed significantly to this risk. Here, a highly sensitive liquid freestanding membrane (FSM) SERS method based on iodide modified silver nanoparticles (Ag NPs) was developed for quantitative detection of insecticide deltamethrin (DM) residues in solution phase samples and on surfaces with good accuracy and high sensitivity. The DM SERS spectrum from 500 to 2500 cm-1 resembled the normal Raman counterpart of solid DM. Similar bands at 563, 1000, 1165, 1207, 1735, and 2253 cm-1 were observed as in the literature. For the quantitative analysis, the strongest peak at 1000 cm-1 that was assigned to the stretching mode of the benzene ring and the deformation mode of C-C was selected. The peak intensity at 1000 cm-1 and the concentration of DM showed excellent linearity from 39 to 5000 ppb with a regression equation I = 649.428 + 1.327 C (correlation coefficient R2 = 0.991). The limit of detection (LOD) of the DM was found to be as low as 11 ppb. Statistical comparison between the proposed and the HPLC methods for the analysis of insecticide deltamethrin (DM) residues in solution phase samples showed no significant difference. DM residue analysis on the surface was mimicked by dropping DM pesticide on the glass surface. It is found that DM exhibited high residue levels up to one week after exposure. This proposed SERS method could find application in the household pesticide residues analysis.

SERS Assays Based on Electrospun Nanofibers: Preparation and Analytical Applications

Surface-enhanced Raman spectroscopy (SERS) is a powerful tool and an up-to-date method of analytical chemistry due to its high sensitivity and fingerprint recognition capabilities. Nowadays SERS due to its label-free detection capabilities is being actively developed in medical fields, for example in the analysis of biologically important substances in different matrixes, for potential on-site detection of toxic substances, food safety, and so on. To get the SERS signal, it is necessary the presence of plasmonic nanostructures in the SERS substrates. Electrospun nanofibers have been an attractive alternative to SERS-platforms due to the diversity of advantages, including ease of preparation, structure flexibility, and others. In this review, we summarized the methods of plasmonic nanostructures incorporating substrate based on electrospun nanofibers. Also, the analytical application of SERS-active electrospun nanofibers with embedded nanostructures focused on biologically significant molecules is observed in detail. Finally, the future outlook in the application of these substrates in bioanalysis as the most promising area in analytical chemistry is presented.

Rapid determination of thiram and atrazine pesticide residues in fruit and aqueous system based on surface-enhanced Raman scattering

In this work, a rapid and sensitive strategy was developed to determine thiram (THI) and atrazine (ATZ) by surface-enhanced Raman scattering (SERS) technology. β-cyclodextrin modified silver nanoparticles (β-CD-AgNPs) were synthesized using β-CD as a reducing agent and encapsulating agent under alkaline conditions and employed as SERS substrate. The existence of β-CD can capture the molecules to form host-guest complex and fix molecular orientation in its cavity, thus ensuring the enhanced SERS signal intensity of THI and ATZ. The linear response extends from 2.56 × 10^-8 to 2.56 × 10^-3 mol/L for THI and 3.08 × 10^-8 to 3.08 × 10^-3 mol/L for ATZ, with the limits of detection (LOD) of 2.42 × 10^-9 mol/L for THI and 7.26 × 10^-9 mol/L for ATZ, respectively. The application of the proposed method in real samples including apple and water were investigated, and the results would help promote the application of SERS technology as a powerful analytical tool for detecting other pesticide residues. It is expected that this SERS strategy will provide great value for rapid detecting pesticide residues in food products and environmental systems.

Increasing charge transfer of SERS by the combination of amorphous Al2O3–Al thin film and ZnO nanorods decorated with Ag nanoparticles for trace detection of metronidazole

In this work, we study the charge transfer improvement by the combination of two semiconductors of SERS. The energy levels of the semiconductor, when combined, become intermediate energy levels that support the charge transfer from the HOMO to the LUMO level, amplifying the Raman signal of the organic molecules. The SERS substrates of Ag/a-Al₂O₃–Al/ZnO nanorods with high sensitivity are prepared for detecting dye rhodamine 6G (R6G) and metronidazole (MNZ) standard. The highly ordered vertically grown ZnO nanorods (NRs) are first developed on a glass substrate by a wet chemical bath deposition method. Then, ZnO NRs are covered with an amorphous oxidized aluminum thin film by a vacuum thermal evaporation method to produce a platform with a large surface area and high charge transfer performance. Finally, silver nanoparticles (NPs) are decorated onto this platform to form an active SERS substrate. The structure, surface morphology, optical properties, and elements in the sample are investigated by Raman spectroscopy, X-ray diffractometry, field-emission scanning electron microscopy (FE-SEM), ultraviolet-visible spectroscopy (UV-vis), reflectance spectroscopy, and energy dispersion X-ray spectroscopy (EDS). Rhodamine 6G is used as a reagent to evaluate the SERS substrates with an analytical enhancement factor (EF) of ∼1.85 × 10¹⁰ at the limit of detection (LOD) of 10⁻¹¹ M. These SERS substrates are used to detect metronidazole standard at a LOD of 0.01 ppm and an EF of 2.2 × 10⁶. The SERS substrate exhibits high sensitivity and stability for promising wide application in chemical, biomedical, and pharmaceutical detection.

In this work, we study the charge transfer improvement by the combination of two semiconductors of SERS.

Engineering an Ag/Au bimetallic nanoparticle-based acetylcholinesterase SERS biosensor for in situ sensitive detection of organophosphorus pesticide residues in food

Developing simple, efficient, and inexpensive method for trace amount organophosphorus pesticides' (OPs) detection with high sensitivity and specificity is of significant importance for guaranteeing food safety. Herein, an Ag/Au bimetallic nanoparticle-based acetylcholinesterase (AChE) surface-enhanced Raman scattering (SERS) biosensor was constructed for in situ simple and sensitive detection of pesticide residues in food. The principle of this biosensor exploited 4-mercaptophenylboronic acid (4-MPBA)-modified Ag/Au bimetallic nanoprobes as SERS signal probe to improve sensitivity and stability. The combination of AChE and choline oxidase (CHO) can hydrolyze acetylcholine (ATCh) to generate H₂O₂. The product of H₂O₂ selectively oxidizes the boronate ester of 4-MPBA, decreasing the Raman intensity of the B-O symmetric stretching. In the presence of OPs, it could inhibit the production of H₂O₂ by destroying the AChE activity, so the reduction of the SERS signal was also alleviated. Based on the principle, an Ag/Au bimetallic nanoparticle-based AChE SERS sensor was established without any complicated pretreatments. Benefiting from the synergistic effects of Ag/Au bimetallic hybrids, a linear detection range from 5×10^-9 to 5×10^-4 M was achieved with a limit of detection down to 1.7×10^-9 M using parathion-methyl (PM) as the representative model of OPs. Moreover, the SERS biosensor uses readily available reagents and is simple to implement. Importantly, the proposed SERS biosensor was used to quantitatively analyze OP residues in apple peels. The levels of OPs detected in real samples by this method were consistent with those obtained using gas chromatography-mass spectrometry (GC-MS), suggesting the proposed assay has great potential applications for OPs in situ detection in food safety fields.

Automatic Multi-Plug Filtration Cleanup Tip-Filtration with Ultra-Performance Liquid Chromatography/Tandem Mass Spectrometry Detection For 22 Pesticide Residues in Typical Vegetables

An automatic multi-plug filtration cleanup (m-PFC) tip-filtration method was developed to reduce the manual operation workload in sample preparation. In this work, m-PFC was based on multi-walled carbon nanotubes mixed with primary secondary amines and anhydrous magnesium sulfate (MgSO4) in a packed column for analysis of pesticide residues followed by ultra-performance liquid chromatography coupled with tandem mass spectrometry. Method validation was performed on 22 pesticide residues in carrot, spinach and leek, at spiked levels of 5, 10 and 50 μg/kg, respectively. The average recoveries were between 70.1 and 119.5% with associated relative standard deviations <20% (n = 6) indicating satisfactory accuracy and repeatability. Matrix-matched calibration curves were performed with the correlation coefficients (R2) higher than 0.9903 within a linearity range of 5-100 ng/mL. The limits of quantification were 5 μg/kg for all the pesticides in carrot, spinach and leek matrices. The developed method was successfully used to determine pesticide residues in market samples.

SERS-Based Immunoassay of Myocardial Infarction Biomarkers on a Microfluidic Chip with Plasmonic Nanostripe Microcones

We developed a new plasmonic nanostripe microcone array (PNMA) substrate-integrated microfluidic chip for the simultaneous surface-enhanced Raman scattering (SERS)-based immunoassay of the creatine kinase MB isoenzyme (CK-MB) and cardiac troponin (cTnI) cardiac markers. The conventional immunoassay usually employs a microtiter plate as the solid capture plate to form the immunocomplexes. However, the two-dimensional (2D) surface of the microtiter plate limits the capture efficiency of the target antigens due to the steric hindrance effect. To address this issue, a gold film-coated microcone array with nanostripes was developed that can provide a large surface area for capture antibody conjugation and serve as a SERS-active substrate. This unique nano-microhierarchical structure showed an excellent light trapping effect and induced surface plasmon resonance to further enhance the Raman signals of the SERS nanoprobes. It significantly improved the sensitivity and applicability of SERS-based immunoassay on the microfluidic chip. With this integrated microfluidic chip, we successfully performed the simultaneous detection of CK-MB and cTnI, and the detection limit can reach 0.01 ng mL^-1. It is believed that the PNMA substrate-integrated microfluidic chip would play a critical role in the rapid and sensitive diagnostics of cardiac diseases.

Recent Progress in Nanotechnology-Based Approaches for Food Monitoring

Throughout the food supply chain, including production, storage, and distribution, food can be contaminated by harmful chemicals and microorganisms, resulting in a severe threat to human health. In recent years, the rapid advancement and development of nanotechnology proposed revolutionary solutions to solve several problems in scientific and industrial areas, including food monitoring. Nanotechnology can be incorporated into chemical and biological sensors to improve analytical performance, such as response time, sensitivity, selectivity, reliability, and accuracy. Based on the characteristics of the contaminants and the detection methods, nanotechnology can be applied in different ways in order to improve conventional techniques. Nanomaterials such as nanoparticles, nanorods, nanosheets, nanocomposites, nanotubes, and nanowires provide various functions for the immobilization and labeling of contaminants in electrochemical and optical detection. This review summarizes the recent advances in nanotechnology for detecting chemical and biological contaminations in the food supply chain.

Syntheses of APTMS-Coated ZnO: An Investigation towards Penconazole Detection

Extrinsic chemiluminescence can be an efficient tool for determining pesticides and fungicides, which do not possess any intrinsic fluorescent signal. On this basis, (3-aminopropyl) trimethoxysilane (APTMS)-coated ZnO (APTMS@ZnO) was synthesized and tested as an extrinsic probe for the fungicide penconazole. Several synthetic routes were probed using either a one-pot or two-steps method, in order to ensure both a green synthetic pathway and a good signal variation for the penconazole concentration. The synthesized samples were characterized using X-ray diffraction (XRD), infrared (IR), Raman and ultraviolet-visible (UV-Vis) spectroscopy, scanning electron microscopy (SEM) imaging and associated energy-dispersive X-ray (EDX) analysis. The average size of the synthesized ZnO nanoparticles (NPs) is 54 ± 10 nm, in line with previous preparations. Of all the samples, those synthesized in two steps, at temperatures ranging from room temperature (RT) to a maximum of 40 °C, using water solvent (G-APTMG@ZnO), appeared to be composed of nanoparticles, homogeneously coated with APTMS. Chemiluminescence tests of G-APTMG@ZnO, in the penconazole concentration range 0.7-1.7 ppm resulted in a quenching of the native signal between 6% and 19% with a good linear response, thus indicating a green pathway for detecting the contaminant. The estimated detection limit (LOD) is 0.1 ± 0.01 ppm.