Surface Enhanced Raman Spectroscopy for In-Field Detection of Pesticides: A Test on Dimethoate Residues in Water and on Olive Leaves

Study on the Rapid Limit Test for Six Sulfonamide Residues in Food Based on the TLC-SERS Method

Sulfonamides are not only widely applied in clinics but also highly valued in animal husbandry. Recently, it has become common for sulfonamide residues to exceed the standard limits in food, which can affect human health. Current regulations limit these residues. Therefore, we constructed a new limit test method to rapidly determine the levels of sulfonamide residues. Six sulfonamides were detected using the latest method called TLC-SERS, namely, sulfamethasone (A), sulfamethazine (B), sulfadoxine (C), sulfamethoxydiazine (D), sulfamethoxazole (E), and sulfathiazole (F). The optimal conditions for SERS detection were investigated for these six drugs, and the separation effects of different TLC spreaders on them were compared. Then, we successfully established a separation system using dichloromethane-methanol-ammonia in a ratio of 5:1:0.25 (v/v/v), which provided good separation effects on the six drugs. The residues were preliminarily separated via TLC. A silver sol solution was added to the spot on the silica gel G plate at the corresponding specific shift values, and SERS detection was performed. The sample solution was placed on the spot under a 532 nm laser, and the SERS spectrum was collected and analyzed for the six sulfonamides. The results showed obvious variations in the SERS spectrum among the six sulfonamides, with the LODs being 12.5, 6.4, 6.3, 7.1, 18.8, and 6.2 ng/mL from A to F, respectively, and an RSD of <3.0%. Within 48 h, the SERS signal for each sulfonamide drug was kept stable, with an RSD of <3.0%. The detection results of 20 samples using the TLC-SERS method were consistent with those obtained by UPLC-MS/MS. The established TLC-SERS method is simple and fast, providing a useful reference for the rapid detection of residue limits in food.

Ti3C2Tx MXene-Based Fluorescent Aptasensor for Detection of Dimethoate Pesticide

Dimethoate contaminants in food pose a threat to human health. Rapid and sensitive trace detection methods are required to keep food safe. In this study, a novel fluorescent aptasensor was developed for the sensitive detection of dimethoate based on carbon quantum dots labeled with double-stranded DNA (CQDs-apt-cDNA) and Ti3C2Tx flakes. Under optimal conditions, the aptasensor showed a good linear range of 1 × 10-9 to 5 × 10-5 M for dimethoate with a coefficient of determination (R2) of 0.996. Besides, a low detection limit of 2.18 × 10-10 M was obtained. The aptasensor showed high selectivity in interference samples and good reproducibility with an RSD of 3.06% (<5%) for dimethoate detection. Furthermore, the proposed aptasensor was applied to the detection of dimethoate in apple juice and tap water with satisfactory recoveries from 96.2 to 104.4%. Because of these benefits, this aptasensor has the potential and promise for detecting food contaminants in the food industry.

Exploring Bacterial and Fungal Biodiversity in Eight Mediterranean Olive Orchards (Olea europaea L.) in Tunisia

A wide array of bacteria and fungi are known for their association with pests that impact the health of the olive tree. The latter presents the most economically important cultivation in Tunisia. The microbial diversity associated with olive orchards in Tunisia remains unknown and undetermined. This study investigated microbial diversity to elucidate the microbial interactions that lead to olive disease, and the bio-prospects for potential microbial biocontrol agents associated with insect pests of economic relevance for olive cultivation in the Mediterranean area. Bacterial and fungal isolation was made from soil and olive tree pests. A total of 215 bacterial and fungal strains were randomly isolated from eight different biotopes situated in Sfax (Tunisia), with different management practices. 16S rRNA and ITS gene sequencing were used to identify the microbial community. The majority of the isolated bacteria, Staphylococcus, Bacillus, Alcaligenes, and Providencia, are typical of the olive ecosystem and the most common fungi are Penicillium, Aspergillus, and Cladosporium. The different olive orchards depicted distinct communities, and exhibited dissimilar amounts of bacteria and fungi with distinct ecological functions that could be considered as promising resources in biological control.

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).

Nanotechnology in food and water security: on-site detection of agricultural pollutants through surface-enhanced Raman spectroscopy

Agricultural pollutants are harmful components threatening human health, wildlife, the environment, and the ecosystem. To avoid their exposure, developing prevention and detection systems with high sensitivity and selectivity is required. Most conventional methods, including molecular and chromatographic techniques, cannot be adopted for outdoor on-site detection even though they can provide sensitive and selective detection. Thus, detection platforms that can provide on-site detection via miniaturized and high throughput systems should be developed. As an alternative method, surface-enhanced Raman scattering (SERS) provides unique information about the substances in the presence of plasmonic nanostructures, and it can be portable with the use of portable detection systems and spectrometers. In this study, on-site detection of agricultural pollutants through SERS is reviewed. Three different types of agricultural pollutants were pointed out. On-site detection of biological pollutants, including bacteria and viruses, is reviewed as the first type of pollutant. As a second type, the detection of pesticides, antibiotics, and additives are focused on as chemical pollutants. The third group includes the detection of microplastics and also nanoparticles from the environment.

Effect of the Duty Cycle of Flower-like Silver Nanostructures Fabricated with a Lyotropic Liquid Crystal on the SERS Spectrum

Surface-enhanced Raman scattering (SERS) has been widely reported to improve the sensitivity of Raman spectra. Ordinarily, the laser is focused on the sample to measure the Raman spectrum. The size of the focused light spot is comparable with that of micro-nano structures, and the number of micro-nano structures contained in the light spot area (defined as duty cycle) will severely affect the spectrum intensity. In this study, flower-like silver nanostructures were fabricated with a soft lyotropic liquid crystal template in order to investigate the effect of duty cycle. They were observed under a scanning electron microscope, and their spectrum enhancement factor was computed with the obtained Raman spectrum. Then, their duty cycles were measured using a SERS substrate at different locations. A formula was derived to represent the relation between the duty cycle of the nanoflowers and the Raman spectral intensity. This work could promote the actual applications of SERS in high-sensitivity spectrum testing.

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.

Detection of multi-class pesticide residues with surface-enhanced Raman spectroscopy

The excessive use of pesticides disturbs the natural balance in the environment, creates resistance to pesticides and leads to water and food contamination. Therefore, the implementation of fast, robust and cost effective techniques for the monitoring of pesticides is required. In this work surface-enhanced Raman spectroscopy (SERS) was used for the detection of four common pesticides: atrazine, simazin, irgarol, and diuron. SERS is nowadays considered an effective technique for detection of various analytes in low concentration. Sensitivity of the SERS method depends on the type of substrate that can be either a colloidal solution of metal nanoparticles (NPs) or a metal surface with a suitable nanostructured topology. Here, we have investigated the application of silver nanospheres and silver nanoprisms as SERS substrates in pesticides detection. Colloids with spherical NPs were produced by chemical reduction while Ag nanoprisms were prepared by reducing silver nitrate with borohydride (with citrate as a stabilizing agent) and stirring under a UV lamp for 4 and 10 h. The SERS results have shown that, in the presence of synthesized NPs, it was possible to detect millimolar concentrations of aforementioned pesticides with the exception of diuron.

Onsite/on-field analysis of pesticide and veterinary drug residues by a state-of-art technology: A review

Pesticides and veterinary drugs are generally employed to control pests and insects in crop and livestock farming. However, remaining residues are considered potentially hazardous to human health and the environment. Therefore, regular monitoring is required for assessing and legislation of pesticides and veterinary drugs. Various approaches to determining residues in various agricultural and animal food products have been reported. Most analytical methods involve sample extraction, purification (cleanup), and detection. Traditional sample preparation is time-consuming labor-intensive, expensive, and requires a large amount of toxic organic solvent, along with high probability for the decomposition of a compound before the analysis. Thus, modern sample preparation techniques, such as the quick, easy, cheap, effective, rugged, and safe method, have been widely accepted in the scientific community for its versatile application; however, it still requires a laboratory setup for the extraction and purification processes, which also involves the utilization of a toxic solvent. Therefore, it is crucial to elucidate recent technologies that are simple, portable, green, quick, and cost-effective for onsite and infield residue detections. Several technologies, such as surface-enhanced Raman spectroscopy, quantum dots, biosensing, and miniaturized gas chromatography, are now available. Further, several onsite techniques, such as ion mobility-mass spectrometry, are now being upgraded; some of them, although unable to analyze field sample directly, can analyze a large number of compounds within very short time (such as time-of-flight and Orbitrap mass spectrometry). Thus, to stay updated with scientific advances and analyze organic contaminants effectively and safely, it is necessary to study all of the state-of-art technology.

Surface-Enhanced Raman Spectroscopy for Bisphenols Detection: Toward a Better Understanding of the Analyte-Nanosystem Interactions

Silver nanoparticles functionalized with thiolated β-cyclodextrin (CD-SH) were employed for the detection of bisphenols (BPs) A, B, and S by means of surface-enhanced Raman spectroscopy (SERS). The functionalization of Ag nanoparticles with CD-SH leads to an improvement of the sensitivity of the implemented SERS nanosensor. Using a multivariate analysis of the SERS data, the limit of detection of these compounds was estimated at about 10⁻⁷ M, in the range of the tens of ppb. Structural analysis of the CD-SH/BP complex was performed by density functional theory (DFT) calculations. Theoretical results allowed the assignment of key structural vibrational bands related to ring breathing motions and the inter-ring vibrations and pointed out an external interaction due to four hydrogen bonds between the hydroxyl groups of BP and CD located at the external top of the CD cone. DFT calculations allowed also checking the interaction energies of the different molecular species on the Ag surface and testing the effect of the presence of CD-SH on the BPs’ affinity. These findings were in agreement with the experimental evidences that there is not an actual inclusion of BP inside the CD cavity. The SERS sensor and the analysis procedure of data based on partial least square regression proposed here were tested in a real sample consisting of the detection of BPs in milk extracts to validate the detection performance of the SERS sensor.

Optical Screening Methods for Pesticide Residue Detection in Food Matrices: Advances and Emerging Analytical Trends

Pesticides have been extensively used in agriculture to protect crops and enhance their yields, indicating the need to monitor for their toxic residues in foodstuff. To achieve that, chromatographic methods coupled to mass spectrometry is the common analytical approach, combining low limits of detection, wide linear ranges, and high accuracy. However, these methods are also quite expensive, time-consuming, and require highly skilled personnel, indicating the need to seek for alternatives providing simple, low-cost, rapid, and on-site results. In this study, we critically review the available screening methods for pesticide residues on the basis of optical detection during the period 2016-2020. Optical biosensors are commonly miniaturized analytical platforms introducing the point-of-care (POC) era in the field. Various optical detection principles have been utilized, namely, colorimetry, fluorescence (FL), surface plasmon resonance (SPR), and surface enhanced Raman spectroscopy (SERS). Nanomaterials can significantly enhance optical detection performance and handheld platforms, for example, handheld SERS devices can revolutionize testing. The hyphenation of optical assays to smartphones is also underlined as it enables unprecedented features such as one-click results using smartphone apps or online result communication. All in all, despite being in an early stage facing several challenges, i.e., long sample preparation protocols or interphone variation results, such POC diagnostics pave a new road into the food safety field in which analysis cost will be reduced and a more intensive testing will be achieved.

An efficient LSPR method to quantitatively detect dimethoate: Development, characterization and evaluation

In recent years, there has been growing concern among consumers about pesticide contamination in fruits. Therefore, rapid, reliable, and consistent detection methods for OPPs, especially dimethoate, are crucially needed. The existing quantitative methods for detecting dimethoate are not suitable for rapid measuring system such as the dimethoate samples from two channels. Hence this paper examines the utilization of a dual-channel system for utilize the absorption variations of the Localized Surface Plasmon Resonance (LSPR) bands of gold nanoparticles (AuNPs) were investigate for detection of dimethoate. Under optimized conditions, the relationship between concentrations of dimethoate and absorbance ratios (A(520)/A(640)) was linearly found in the concentration range of 10–100 nM. Result from the experiment shows that both channels exhibit a linear correlation coefficient as high as 0.97 and a limit of detection (LOD) as low as 5.5 nM. This LSPR detection system was characterized by testing the dimethoate in apple samples and the recovery rates were found to be in the range of 85.90% to 107.37%. The proposed dual-channel LSPR system for detecting dimethoate creating a new approach for detecting organophosphate insecticide in agricultural fields. It could lay the foundation for designing a high-throughput analysis of the insecticides using a wavelength division multiplexing switch (WDMS).

Rapid and ultrasensitive detection of food contaminants using surface-enhanced Raman spectroscopy-based methods

With the globalization of food and its complicated networking system, a wide range of food contaminants is introduced into the food system which may happen accidentally, intentionally, or naturally. This situation has made food safety a critical global concern nowadays and urged the need for effective technologies capable of dealing with the detection of food contaminants as efficiently as possible. Hence, Surface-enhanced Raman spectroscopy (SERS) has been taken as one of the primary choices for this case, due to its extremely high sensitivity, rapidity, and fingerprinting interpretation capabilities which account for its competency to detect a molecule up to a single level. Here in this paper, we present a comprehensive review of various SERS-based novel approaches applied for direct and indirect detection of single and multiple chemical and microbial contaminants in food, food products as well as water. The aim of this paper is to arouse the interest of researchers by addressing recent SERS-based, novel achievements and developments related to the investigation of hazardous chemical and microbial contaminants in edible foods and water. The target chemical and microbial contaminants are antibiotics, pesticides, food adulterants, Toxins, bacteria, and viruses. In this paper, different aspects of SERS-based reports have been addressed including synthesis and use of various forms of SERS nanostructures for the detection of a specific analyte, the coupling of SERS with other analytical tools such as chromatographic methods, combining analyte capture and recognition strategies such as molecularly imprinted polymers and aptasensor as well as using multivariate statistical analyses such as principal component analysis (PCA)to distinguish between results. In addition, we also report some strengths and limitations of SERS as well as future viewpoints concerning its application in food safety.

Patterned Superhydrophobic SERS Substrates for Sample Pre-Concentration and Demonstration of Its Utility through Monitoring of Inhibitory Effects of Paraoxon and Carbaryl on AChE

We describe a patterned surface-enhanced Raman spectroscopy (SERS) substrate with the ability to pre-concentrate target molecules. A surface-adsorbed nanosphere monolayer can serve two different functions. First, it can be made into a SERS platform when covered by silver. Alternatively, it can be fashioned into a superhydrophobic surface when coated with a hydrophobic molecular species such as decyltrimethoxy silane (DCTMS). Thus, if silver is patterned onto a latter type of substrate, a SERS spot surrounded by a superhydrophobic surface can be prepared. When an aqueous sample is placed on it and allowed to dry, target molecules in the sample become pre-concentrated. We demonstrate the utility of the patterned SERS substrate by evaluating the effects of inhibitors to acetylcholinesterase (AChE). AChE is a popular target for drugs and pesticides because it plays a critical role in nerve signal transduction. We monitored the enzymatic activity of AChE through the SERS spectrum of thiocholine (TC), the end product from acetylthiocholine (ATC). Inhibitory effects of paraoxon and carbaryl on AChE were evaluated from the TC peak intensity. We show that the patterned SERS substrate can reduce both the necessary volumes and concentrations of the enzyme and substrate by a few orders of magnitude in comparison to a non-patterned SERS substrate and the conventional colorimetric method.

A simple spectroscopic method to determine dimethoate in water samples by complex formation

A simple and rapid method for the determination of dimethoate in water was developed based on the monitoring of the complex formation between bis 5-phenyldipyrrinate of nickel (II) and the herbicide dimethoate. The method showed a short response time (10 s), high selectivity (very low interference from other sulfate and salts), high sensitivity (limit of detection (LOD) 0.45 µM, limit of quantitation (LOQ) of 1.39 µM), and a K_d of 2.4 µM. Stoichiometry experiments showed that complex formation occurred with a 1:1 relation. The method was applied to different environmental water samples such as lagoon, stream, urban, and groundwater samples. The results indicated that independently from the water source, the method exhibited high precision (0.25-2.47% variation coefficient) and accuracy (84.42-115.68% recovery). In addition, the method was also tested using an effluent from a wastewater treatment plant from Mexico; however, the results indicated that the presence of organic matter had a pronounced effect on the detection.

Challenges in SERS-based pesticide detection and plausible solutions

Surface-enhanced Raman spectroscopy (SERS) can be used for the detection of trace amounts of pesticides in foods to ensure consumer safety. In this perspective, we highlight the trends of SERS-based assays in pesticide detection and the various challenges associated with their selectivity, reproducibility, and nonspecific binding. We also discuss and compare the target analyte capture techniques, such as the use of antibodies, aptamers, and molecularly imprinted polymers (MIPs), coupled with SERS to overcome the drawbacks as mentioned above. In addition, issues related to the nonspecific binding of analytes and its potential solution are discussed.

Surface-Enhanced Raman Scattering Detection of Fipronil Pesticide Adsorbed on Silver Nanoparticles

This work presents a surface-enhanced Raman scattering (SERS) and density functional theory (DFT) study of a fipronil adsorbed on colloidal silver nanoparticles (AgNPs). A standard curve was established to quantify fipronil within a range of 0.0001⁻0.1 ppm (r² ≥ 0.985), relying on the unique fipronil Raman shift at ~2236 cm^-1 adsorbed on AgNPs. DFT calculations suggest that the nitrile moiety (C≡N) binding should be slightly more favorable, by 1.92 kcal/mol, than those of the nitrogen atom of the pyrazole in fipronil and Ag₆ atom clusters. The characteristic peaks of the SERS spectrum were identified, and both the calculated vibrational wavenumbers and the Raman intensity pattern were considered. The vibrational spectra of fipronil were obtained from the potential energy distribution (PED) analysis and selective Raman band enhancement.