Competitive immunosensor for sensitive and optical anti-interference detection of imidacloprid by surface-enhanced Raman scattering

ZIF-8-wrapped AgNPs modified with β-cyclodextrin for sensitive detection of thiacloprid and imidacloprid by SERS technology

The high efficient surface-enhanced Raman scatterring (SERS) methods to detect thiacloprid and imidacloprid were established using ZIF-8-wrapped Ag nanoparticles (AgNPs) modified with β-cyclodextrin (β-CD). The substrate of ZIF-8/β-CD@AgNPs was characterized by ultraviolet visible spectra (UV-vis), thermogravimetric analysis (TGA), X-ray diffraction (XRD), transmission electron microscopy (TEM) and scanning transmission electron microscopy (STEM). The interaction between the substrate and thiacloprid/imidacloprid was also explored. The optimum measurement conditions were obtained by response surface model based on single-factor experiments. Enhancement factors (EFs) of thiacloprid and imidacloprid were respectively 2.29 × 106 and 2.60 × 106. A good linearity between the scattering intensity and the concentration of thiacloprid/imidacloprid within 3-1000 nmol L-1/6-400 nmol L-1 was established. The interference experiments indicated that the methods had good selectivity. The SERS methods were successfully applied to detect thiacloprid and imidacloprid in several vegetables samples. The recoveries ranged from 95.5 % to 105 % (n = 5). The detection limits (LODs) (S/N = 3) for thiacloprid and imidacloprid were 1.50 and 0.83 nmol L-1, respectively.

Bimetallic AuNR@AgNCs for ultrasensitive surface-enhanced Raman scattering sensing of dithianon in apple juice

In this study, a bimetallic surfaced-enhanced Raman spectroscopy (SERS)-active substrate consisting of AuNR@AgNCs was proposed for the rapid detection of dithianon. Due to the significant synergistic enhancement of the core-shell nanocuboids, the obtained AuNR@AgNC substrate exhibited excellent SERS performance. The simulation findings supported the practical SERS results and demonstrated that interactions were mainly maintained by the nitrile functional group. The AuNR@AgNCs could be used to detect dithianon with an LOD value of 20 nM. Moreover, dithianon in river water and apple juice could be detected with recovery in the satisfactory ranges of 97.41%-98.35% and 97.77%-98.70%, respectively, by using this substrate under optimal conditions, indicating that the AuNR@AgNC substrate could serve as an excellent SERS detection platform for pesticide residues in fruit.

Detection of neonicotinoids in agricultural products using magnetic molecularly imprinted polymers-surface enhanced Raman spectroscopy

In this paper, magnetic molecularly imprinted polymers-surface-enhanced Raman spectroscopy (MMIPs-SERS) for rapidly analyzing acetamiprid and thiacloprid in agricultural products has been firstly developed. The magnetic imprinted polymers were obtained by polymerizing the imprinted layers on the surface of magnetic nanoparticles. The polymers were detailed characterized by using series of analytical techniques, and their adsorption and recognition performance were validated by adsorption tests. The results showed that the magnetic molecularly imprinted polymers possessed typically core-shell structure and exhibited class-specific recognition, fast adsorption saturation (only 1 min), and good magnetic separation performance towards targets. The adsorption and desorption conditions for MMIPs-SERS detection system were carefully investigated. Under optimum conditions, the good linear detection range of 1∼20 μg/g with LODs of 23.7-68.8 ng/g for acetamiprid and thiacloprid in peach and pear samples was obtained. Through the reusable and spiked experiments, the developed MMIPs-SERS method based on Au NPs as enhanced substrate was validated to be highly sensitive, accurate, efficient and applicable in analyzing neonicotinoids from pear and peach samples. This study provided a rapid and simple detection method for neonicotinoids with effective separation and detection properties based on the synergistic effect of imprinted polymers and SERS. More importantly, this developed method have good application potential in rapid analyzing field for neonicotinoids due to the amazing rapid adsorption time for extracting targets from complex food matrix (only 1 min).

Terahertz determination of imidacloprid in soil based on a metasurface sensor

Pesticides in soil are continuously one of the most studied analytes due to their environmental and human health effects. Thus the detection of pesticides in soil is an important means to control and assess soil quality. Here, we theoretically and experimentally present a novel method for the determination of imidacloprid in soil by using a metasurface sensor operating at terahertz frequencies. The metasurface shows a resonance peak at 880 GHz and the electric field at the peak is strongly localized and concentrated in the gap of split I-shaped resonator. The detection of complex refractive index shows that the position and the transmittance of resonance peak are depend on the change in the complex refractive index. The measurement of imidacloprid concentration in soil demonstrates that both the frequency shift and the transmittance change at peak increase almost linearly with the increasing of imidacloprid concentration ranging from 0.25% to 2%. In this case, the frequency shift reaches 97 GHz and the transmittance change at peak is as high as 30.9%. Our work enables the determination of imidacloprid in soil at terahertz frequencies with good reliability and high sensitivity, showing the potential application of terahertz spectroscopy in environmental monitoring.

Research advances of SERS analysis method based on silent region molecules for food safety detection

Food safety is a critical issue that is closely related to people's health and safety. As a simple, rapid, and sensitive detection technique, surface-enhanced Raman scattering (SERS) technology has significant potential for food safety detection. Recently, researchers have shown a growing interest in utilizing silent region molecules for SERS analysis. These molecules exhibit significant Raman scattering peaks in the cellular Raman silent region between 1800 and 2800 cm-1 avoiding overlapping with the SERS spectrum of biological matrices in the range 600-1800 cm-1, which could effectively circumvent matrix effects and improve the SERS accuracy. In this review, the application of silent region molecules-based SERS analytical technique for food safety detection is introduced, detection strategies including label-free detection and labeled detection are discussed, and recent applications of SERS analysis technology based on molecules containing alkyne and nitrile groups, as well as Prussian blue (PB) in the detection of pesticides, mycotoxins, metal ions, and foodborne pathogens are highlighted. This review aims to draw the attention to the silent region molecules-based SERS analytical technique and to provide theoretical support for its further applications in food safety detection.

An interference-free SERS-based aptasensor for chlorpyrifos detection

In this study, we propose an interference-free SERS-based aptasensor for trace detection of chlorpyrifos (CPF) in real samples. In the aptasensor, gold nanoparticles coated with Prussian blue (Au@PB NPs) were employed as SERS tags to provide a sole and intense Raman emission at 2160 cm^-1, which could avoid overlapping with the Raman spectrum of the real samples in 600-1800 cm^-1 to improve the anti-matrix effect ability of the aptasensor. Under the optimum conditions, this aptasensor displayed a linear response for CPF detection in the range of 0.1-316 ng mL^-1 with a low detection limit of 0.066 ng mL^-1. In addition, the prepared aptasensor shows excellent application to determine CPF in cucumber, pear and river water samples. The recovery rates were highly correlated with high-performance liquid chromatography‒mass spectrometry (HPLC‒MS/MS). This aptasensor shows interference-free, specific and sensitive detection for CPF and offers an effective strategy for other pesticide residue detection.

Multicolor aptasensors for pesticide multiresidues detection in agricultural products using bioorthogonal surface-enhanced Raman scattering tags

Realizing accurate pesticide multiresidue detection in a complex matrix is still a challenge for point-of-care sensing methods. Herein, we introduced background-free and multicolor aptasensors based on bioorthogonal surface-enhanced Raman scattering (SERS) tags and successfully applied them to analyze multiple pesticide residues. The excellent anti-interference and multiplex capability are due to the application of three bioorthogonal Raman reporters involving 4-ethenylbenzenamine (4-EBZM), Prussian blue (PB) and 2-amino-4-cyanopyridine (AMCP) with alkynyl and cyano groups, which demonstrated apparent Raman shift peaks at 1993 cm^-1, 2160 cm^-1, and 2264 cm^-1 in the biologically Raman-silent region, respectively. Ultimately, a detection range of 1-50 nM for acetamiprid, atrazine and malathion was achieved with detection limits of 0.39, 0.57 and 0.16 nM, respectively. The developed aptasensors were successfully used to determine pesticide residues in real samples. These proposed multicolor aptasensors offer an effective strategy for pesticide multiresidue detection with advantages of anti-interference, high specificity and high sensitivity.

Switchable aptamer-fueled colorimetric sensing toward agricultural fipronil exposure sensitized with affiliative metal-organic framework

Persistent usage of pesticides in agriculture has posed serious damage to overall ecosystem and human health, and thereby it is imperative to develop sensitive and efficient tools to evaluate residual pesticides in food and environmental setting. Herein, we reported a switchable colorimetric probe toward fipronil residue sensitized with aptamer-fueled catalytic activity of affiliative ZIF-8. Innovatively, it was found that the attached aptamer preferred to adsorb 3,3',5,5'-tetramethylbenzidine (TMB) rather than 2,2-azinobis (3-ethylbenzothiazo-line-6-sulfonic acid) (ABTS), greatly promoting catalytic oxidation of ZIF-8 toward TMB for further improving sensitivity. Aiding with smartphone-based image acquisition, fipronil-responsive discoloration degree was converted into the ratio of green and blue (G/B) with limit of detection as low as 0.036 μM (0.016 μg·g^-1). Moreover, it allowed for fipronil analysis in water, soil and vegetable samples with good recovery between 87 % and 110 %, verifying extension application prospect of the aptamer-fueled colorimetry for on-field pesticide evaluation in food safety supervision.

Giant Enhancement of Raman Scattering by a Hollow-Core Microstructured Optical Fiber Allows Single Exosome Probing

Microstructured optical fibers (MOFs) provide solutions for breaking through the bottlenecks in areas of high-power transmission and high-efficiency optical waveguides. Other than transporting light waves, MOFs can synergistically combine microfluidics and optics in a single fiber with an unprecedented light path length not readily achievable by planar optofluidic configurations. Here, we demonstrate that hollow-core anti-resonant optical fibers (HcARFs) can significantly enhance Raman scattering by over three orders of magnitude (EF ≈ 5000) compared with a planar setup, due to the joint mechanisms of strong light-matter interaction in the fiber core and the cumulative effect of the fiber. The giant enhancement enables us to develop the first optical fiber sensor to achieve single cancer exosome detection via a sandwich-structured strategy. This enables a multiplexed analysis of surface proteins of exosome samples, potentially allowing an accurate identification of the cellular origin of exosomes for cancer diagnosis. Our findings could expand the applications of HcARF in many exciting areas beyond the waveguide.

Electrochemical activation of oxygen vacancy-rich TiO2@MXene as high-performance electrochemical sensing platform for detecting imidacloprid in fruits and vegetables

Heterostructured TiO₂@MXene rich in oxygen vacancies defects (VO-TiO₂@MXene) has been developed to construct an electrochemical sensing platform for imidacloprid (IMI) determination. For the material design, TiO₂ nanoparticles were firstly in situ grown on MXene and used as a scaffolding to prevent the stack of MXene nanosheets. The obtained TiO₂@MXene heterostructure displays excellent layered structure and large specific surface area. After that, electrochemical activation is utilized to treat TiO₂@MXene, which greatly increases the concentration of surface oxygen vacancies (VOs), thereby remarkably enhancing the conductivity and adsorption capacity of the composite. Accordingly, the prepared VO-TiO₂@MXene displays excellent electrocatalytic activity toward the reduction of IMI. Under optimum conditions, cyclic voltammetry and linear sweep voltammetry techniques were utilized to investigate the electrochemical behavior of IMI at the VO-TiO₂@MXene/GCE. The proposed sensor based on VO-TiO₂@MXene presents an obvious reduction peak at -1.05 V(vs. Hg|Hg₂Cl₂) with two linear ranges from 0.07 - 10.0 μM and 10.0 - 70.0 μM with a detection limit of 23.3 nM (S/N= 3). Furthermore, the sensor provides a reliable result for detecting IMI in fruit and vegetable samples with a recovery of 97.9-103% and RSD≤ 4.3%. A sensitive electrochemical sensing platform was reported for imidacloprid (IMI) determination based on heterostructured TiO₂@MXene rich in oxygen vacancy defects.

Optical sensing techniques for rapid detection of agrochemicals: Strategies, challenges, and perspectives

In recent years, the irrational use of agrochemicals has caused great harm to the environment and public health. Along with the rapid development of optical technology and nanotechnology, the research of optical sensing methods in agrochemical detection has been developed rapidly owing to its advantages of simplicity, fast response, and cost-effectiveness. In this review, the strategies of employing optical systems based on colorimetric sensor, fluorescence, chemiluminescence, terahertz spectroscopy, surface plasmon resonance, and surface-enhanced Raman spectroscopy for sensing agrochemicals were summarized. In addition, the challenges in the practical application of optical sensing technologies for agrochemical detection were discussed in-depth, and potential future trends and prospects of these techniques were addressed. A variety of nanomaterials have been developed for enhancing the sensitivity of optical sensing systems. The optical properties of nanomaterials are governed by their size, shape, and chemical structure. Although each optical sensing system holds its advantages, there are still many challenges that need to be overcome in practical applications. With the continuous developments in novel functional nanomaterials, sample preparation methods, and spectral processing algorithms, optical sensors are expected to have powerful potential for rapid testing of agrochemicals in the environment and foods.

Recent progress in organic-inorganic hybrid materials as absorbents in sample pretreatment for pesticide detection

Sample pretreatment is essential for trace analysis of pesticides in complex food and environment matrices. Recently, organic-inorganic hybrid materials have gained increasing attention in pesticide extraction and preconcentration. This review highlighted the common organic-inorganic hybrid materials used as absorbents in sample pretreatment for pesticide detection. Furthermore, the preparation and characterization of organic-inorganic hybrid materials were summarized. To obtain a deep understanding of adsorption toward target analytes, the adsorption mechanism and absorption evaluation were discussed. Finally, the applications of organic-inorganic hybrid materials in sample pretreatment techniques and perspectives in the future are also discussed.

Rapid Detection of Carbendazim Residue in Apple Using Surface-Enhanced Raman Scattering and Coupled Chemometric Algorithm

In order to achieve rapid and precise quantification detection of carbendazim residues, surface-enhanced Raman spectroscopy (SERS) combined with variable selected regression methods were developed. A higher sensitivity and greater density of "hot spots" in three-dimensional (3D) SERS substrates based on silver nanoparticles compound polyacrylonitrile (Ag-NPs @PAN) nanohump arrays were fabricated to capture and amplify the SERS signal of carbendazim. Four Raman spectral variable selection regression models were established and comparatively assessed. The results showed that the bootstrapping soft shrinkage-partial least squares (BOSS-PLS) method achieved the best predictive capacity after variable selection, and the final BOSS-PLS model has the correlation coefficient (R_P) of 0.992. Then, this method used to detect the carbendazim residue in apple samples; the recoveries were 86~116%, and relative standard deviation (RSD) is less than 10%. The 3D SERS substrates combined with the BOSS-PLS algorithm can deliver a simple and accurate method for trace detection of carbendazim residues in apples.

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.