Strategies for SERS Detection of Organochlorine Pesticides

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.

Integrating transformer-based machine learning with SERS technology for the analysis of hazardous pesticides in spinach

This study introduces an innovative strategy for the rapid and accurate identification of pesticide residues in agricultural products by combining surface-enhanced Raman spectroscopy (SERS) with a state-of-the-art transformer model, termed SERSFormer. Gold-silver core-shell nanoparticles were synthesized and served as high-performance SERS substrates, which possess well-defined structures, uniform dispersion, and a core-shell composition with an average diameter of 21.44 ± 4.02 nm, as characterized by TEM-EDS. SERSFormer employs sophisticated, task-specific data processing techniques and CNN embedders, powered by an architecture features weight-shared multi-head self-attention transformer encoder layers. The SERSFormer model demonstrated exceptional proficiency in qualitative analysis, successfully classifying six categories, including five pesticides (coumaphos, oxamyl, carbophenothion, thiabendazole, and phosmet) and a control group of spinach data, with 98.4% accuracy. For quantitative analysis, the model accurately predicted pesticide concentrations with a mean absolute error of 0.966, a mean squared error of 1.826, and an R2 score of 0.849. This novel approach, which combines SERS with machine learning and is supported by robust transformer models, showcases the potential for real-time pesticide detection to improve food safety in the agricultural and food industries.

Fluorescence enhancing and quenching signal based on new approach for selective detection of multiple organochlorine pesticides using blue emissive-carbon dot

Measuring the concentration of organochlorine pesticides (OCPs) in agriculture has engaged significant awareness for healthcare investigation since OCPs are harmful to many physiological processes. Excessive usage of these compounds can result in major contamination of the environment and food supply chains. As a result, more accurate and rapid ways to detect pesticide residues in food are required. In this work, we have portrayed the surface-engineered fluorescent blue emissive-carbon dot (B-CD) with a high quantum yield (49.3 %) via the hydrothermal method for fluorescent sensing of OCPs on real samples. The amine group functionalities of carbon dots have supported the direct coordination with -Cl and -OH groups of HEP, ENS, CDF and 2,4-DPAC for the sensitive detection of OCPs, by switching in the fluorescent intensity of B-CD. The functional group of OCPs exhibits a variety of binding interactions with B-CD to contribute a complex formation, which leads to static quenching via an insubstantial restricted electron transfer process. The synthesized carbon dots exhibit individuality in binding nature towards different OCPs. Fluorescence studies help to distinguish the target OCPs and their low detection limits (LODs) were 0.002, 0.099, 0.16 and 0.082 μM for Heptachlor (HEP - turn "on"), Endosulfan (ENS), Chlordimeform (CDF) and 2,4-dichlorophenoxyacetic acid (2,4-DPAC - turn "off") OCPs respectively. The real water samples and agriculture food samples were effectively investigated and the OCP toxicity was noted. Thus, the design of the fluorescence sensor is established as an easy and proficient sensing method for detecting OCPs.

Different sized gold nanoparticles for array-based sensing of pesticides and its application for strawberry pollution monitoring

The use of pesticides plays an essential role in improving crop quality and yield, however, it causes air, water, and soil pollution and the residue of these pesticides in agricultural products threatens the ecosystem and human life. Therefore, it is highly desirable to develop rapid, simple, and cost-effective methods for regular monitoring of pesticide residues in agricultural products especially strawberry that is consumed fresh and unpeeled. In this study, gold nanoparticles (AuNPs) of varying sizes have been exploited as sensing units to design a non-enzymatic colorimetric sensor array for the detection and discrimination of various pesticides including; bifenazate (BF), paraquat (PQ), diazinon (DZ), thiometon (TM), and carbendazim (CD) and chlorpyrifos (CP). Because of their strong size- and environmentally-dependent properties, AuNPs with different sizes produced distinguished plasmonic patterns in the presence of pesticides at a vast range of concentrations (25-800 ng mL-1). Plasmonic patterns of sensor units have been analyzed by various data visualization (bar plots and heat maps) and pattern recognition methods (linear discriminant analysis (LDA)). The multivariate calibrations showed linear responses ranging from 50 to 800 ng mL-1 for carbendazim, chlorpyrifos, paraquat, and bifenazate and 25-800 ng mL-1 for diazinon and thiometon. The limit of detection (LOD) was calculated to be 17.7, 22.8, 22.4, 9.7, 7.4, and 23.8 ng mL-1 for carbendazim, chlorpyrifos, paraquat, diazinon, thiometon, and bifenazate respectively. Finally, the applicability of the designed sensor was evaluated in real samples comprising tap water, well water, soil, and fruit, leave, drainage water, and culture substrate of strawberry.

Electric Potential Induced Prevention and Removal of an Algal Biofoulant from Planar SERS Substrates

Ulva zoospores are widespread marine macroalgae and a common organism found in biofouling communities due to their strong adhesive properties and quick settlement times. Using Ulva as a model organism, a strategy is presented where direct-current (DC) electric potentials are applied in conjunction with surface-enhanced Raman spectroscopy (SERS) to characterize, remove, and prevent Ulva from forming a biofilm on gold-capped nanopillar SERS substrates. Experiments were conducted within a poly(tetrafluoroethylene) (PTFE) flow channel device where the SERS substrates were used as an electrode. Ulva density, determined in situ by SERS and ex situ by electron and fluorescence microscopy, decreased under successively increasing low negative potentials up to -1.0 V. The presence of damaged Ulva suggests that the applied potential led to spore rupture. At the highest negative applied potential (-1.0 V), microparticles containing copper, which is known for its antimicrobial properties, were associated with Ulva on the SERS substrate and the lowest Ulva density was observed. These findings indicate that (1) SERS can be employed to study biofilm formation on nanostructured metal surfaces and (2) applying low-voltage electric potentials may be used to control Ulva biofouling on SERS marine sensors.

Miniaturized kapok fiber-supported liquid extraction for convenient extraction of pesticide residues in vegetable oils: Determination of organochlorine pesticides as a proof-of-concept study

In this paper, a miniaturized kapok fiber-supported liquid extraction (mini-KF-SLE) method was proposed for selective extraction of pesticide residues in vegetable oils. The natural kapok fiber was used as an inert oil support material based on its hydrophobic and lipophilic properties, and the extraction device was conveniently constructed by loading 15 mg of kapok fiber at the lower middle part of a 1-mL pipette tip. The vegetable oil sample (150 mg) without any pretreatment was directly loaded, followed by the addition of 150 μL of acetonitrile (ACN) as the extractant. After static extraction for 30 min, the extractant was pipetted out with a pipettor. As the proof of concept, it was applied for extracting eight organochlorine pesticides (OCPs) from vegetable oils and the eluate was analyzed by gas chromatography-electron capture detector (GC-ECD). Under optimized conditions, the extraction recoveries of OCPs were calculated to be in ranges of 35.8-79.5%. The satisfied quantitation ability was verified by the established method with coefficients of determination (R²) being greater than 0.99. The limits of detection (LODs) were in ranges of 2.0-50.0 ng/g. The relative recoveries were in ranges of 78.3-117.0% with the inter-/intra-day relative standard deviation (RSD) both being less than 13.3%. The potential of mini-KF-SLE to extract other kinds of pesticides was further verified by the successful extracting three triazole pesticides in vegetable oils with good extraction recoveries (>41.4%). The proposed mini-KF-SLE in combination with instrument detection techniques has the great potential in the low-cost and high-throughput determination of various pesticide residues in vegetable oils.

Nanomaterials for Surface Enhanced Raman Spectroscopy

For many decades, Raman spectroscopy has been disregarded as an ineffective analytical tool because of the very low efficiency of "normal" Raman scattering (the typical cross-section for Raman scattering is about 11 and 8 orders of magnitude smaller than the typical cross-sections for absorption in ultraviolet and infrared wavelengths, respectively [...].

Application of Cotton Swab-Ag Composite as Flexible Surface-Enhanced Raman Scattering Substrate for DMMP Detection

It is both important and required to quickly and accurately detect chemical warfare agents, such as the highly toxic nerve agent sarin. Surface-enhanced Raman scattering (SERS) has received considerable attention due to its rapid results, high sensitivity, non-destructive data acquisition, and unique spectroscopic fingerprint. In this work, we successfully prepared SERS cotton swabs (CSs) for the detection of the sarin simulant agent dimethyl methyl phosphonate (DMMP) by anchoring N1-(3-trimethoxysilylpropyl) diethylenetriamine (ATS)/silver nanoparticle (AgNP) nanocomposites on CSs using ATS as the stabilizer and coupling agent. Simultaneously, the binding mode and reaction mechanics between the AgNP, ATS, and CS were confirmed by XPS. The modified CSs exhibited good uniformity, stability, and adsorption capability for SERS measurements, enabling the adsorption and detection of DMMP residue from an irregular surface via a simple swabbing process, with a detection limit of 1 g/L. The relative standard deviations (RSDs) of RSD₇₁₀ = 5.6% had high reproducibility. In this research, the fabrication method could easily be extended to other cellulose compounds, such as natural fibers and paper. Furthermore, the versatile SERS CSs can be used for the on-site detection of DMMP, particularly in civil and defense applications, to guarantee food security and the health of the population.

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.

Silver Nanoparticle Films Obtained by Convective Self-Assembly for Surface-Enhanced Raman Spectroscopy Analyses of the Pesticides Thiabendazole and Endosulfan

Pesticides pose a great threat to human health and their rapid detection has become an urgent public safety issue engaging the scientific community to search for fast and reliable detection techniques. In this context, Surface Enhanced Raman Spectroscopy (SERS) has emerged as a valuable detection and analysis tool due to its high sensitivity and selectivity, proving its suitability for the food industry and environmental monitoring applications. Here, we report on the fabrication of colloidal silver nanoparticle (AgNP) films by convective self-assembly (CSA) on solid planar substrate and their use for the SERS analyses of two types of pesticides, the fungicide thiabendazole (TBZ) and the insecticide α-endosulfan (α-ES). Electron microscopy shows that these nanoparticle films are dense, highly compact, and uniform across several mm² areas. The SERS efficiency of the fabricated AgNP films is evaluated using a well-known Raman probe, p-aminothiophenol, for multiple excitation laser lines (532 nm, 633 nm, and 785 nm). The films exhibit the largest SERS enhancement factors for 785 nm excitation, reaching values larger than 10⁵. Thiabendazole could be readily adsorbed on the AgNPs without any sample surface functionalization and detected down to 10⁻⁶ M, reaching the sub-ppm range. Endosulfan, a challenging analyte with poor affinity to metal surfaces, was captured near the metal surface by using self-assembled alkane thiol monolayers (hexanethiol and octanethiol), as demonstrated by the thorough vibrational band analysis, and supported by density functional theory (DFT) calculations. In addition, principal component analysis (PCA) based on SERS spectra offers significant leverage in discrimination of the molecules anchored onto the metallic nanostructured surface. This present study demonstrates the utility of self-assembled colloidal nanoparticle films as SERS substrates for a broad range of analytes (para-aminothiophenol, thiabendazole, α-endosulfan, and alkanethiols) and contributes to the development of SERS-based sensors for pesticides detection, identification and monitoring.

Applications of surface-enhanced Raman spectroscopy in environmental detection

As the human population grows, the anthropogenic impacts from various agricultural and industrial processes produce unwanted contaminants in the environment. The accurate, sensitive and rapid detection of such contaminants is vital for human health and safety. Surface-enhanced Raman spectroscopy (SERS) is a valuable analytical tool with wide applications in environmental contaminant monitoring. The aim of this review is to summarize recent advancements within SERS research as it applies to environmental detection, with a focus on research published or accessible from January 2021 through December 2021 including early-access publications. Our goal is to provide a wide breadth of information that can be used to provide background knowledge of the field, as well as inform and encourage further development of SERS techniques in protecting environmental quality and safety. Specifically, we highlight the characteristics of effective SERS nanosubstrates, and explore methods for the SERS detection of inorganic, organic, and biological contaminants including heavy metals, pharmaceuticals, plastic particles, synthetic dyes, pesticides, viruses, bacteria and mycotoxins. We also discuss the current limitations of SERS technologies in environmental detection and propose several avenues for future investigation. We encourage researchers to fill in the identified gaps so that SERS can be implemented in a real-world environment more effectively and efficiently, ultimately providing reliable and timely data to help and make science-based strategies and policies to protect environmental safety and public health.

Advances in Optical Sensors for Persistent Organic Pollutant Environmental Monitoring

Optical chemical sensors are widely applied in many fields of modern analytical practice, due to their simplicity in preparation and signal acquisition, low costs, and fast response time. Moreover, the construction of most modern optical sensors requires neither wire connections with the detector nor sophisticated and energy-consuming hardware, enabling wireless sensor development for a fast, in-field and online analysis. In this review, the last five years of progress (from 2017 to 2021) in the field of optical chemical sensors development for persistent organic pollutants (POPs) is provided. The operating mechanisms, the transduction principles and the types of sensing materials employed in single selective optical sensors and in multisensory systems are reviewed. The selected examples of optical sensors applications are reported to demonstrate the benefits and drawbacks of optical chemical sensor use for POPs assessment.

Development and critical evaluation of a novel fluorescent nanosensor based on a molecularly imprinted polymer for the rapid detection of procymidone in ginseng

Effective methods are required to quantify the organochlorine pesticide procymidone due to its potentially harmful effects toward human health and the environment.

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.

Spatiotemporal Visualization of Insecticides and Fungicides within Fruits and Vegetables Using Gold Nanoparticle-Immersed Paper Imprinting Mass Spectrometry Imaging

Food safety issues caused by pesticide residue have exerted far-reaching impacts on human daily life, yet the available detection methods normally focus on surface residue rather than pesticide penetration to the internal area of foods. Herein, we demonstrated gold nanoparticle (AuNP)-immersed paper imprinting mass spectrometry imaging (MSI) for monitoring pesticide migration behaviors in various fruits and vegetables (i.e., apple, cucumber, pepper, plum, carrot, and strawberry). By manually stamping food tissues onto AuNP-immersed paper, this method affords the spatiotemporal visualization of insecticides and fungicides within fruits and vegetables, avoiding tedious and time-consuming sample preparation. Using the established MSI platform, we can track the migration of insecticides and fungicides into the inner region of foods. The results revealed that both the octanol-water partition coefficient of pesticides and water content of garden stuffs could influence the discrepancy in the migration speed of pesticides into food kernels. Taken together, this nanopaper imprinting MSI is poised to be a powerful tool because of its simplicity, rapidity, and easy operation, offering the potential to facilitate further applications in food analysis. Moreover, new perspectives are given to provide guidelines for the rational design of novel pesticide candidates, reducing the risk of food safety issues caused by pesticide residue.