Enhancing Sensitivity and Selectivity in Pesticide Detection: A Review of Cutting‐Edge Techniques

The primary goal of our review was to systematically explore and compare the state‐of‐the‐art methodologies employed in the detection of pesticides, a critical component of global food safety initiatives. New approach methods in the fields of luminescent nanosensors, chromatography, terahertz spectroscopy, and Raman spectroscopy are discussed as precise, rapid, and versatile strategies for pesticide detection in food items and agroecological samples. Luminescent nanosensors emerge as powerful tools, noted for their portability and unparalleled sensitivity and real‐time monitoring capabilities. Liquid and gas chromatography coupled to spectroscopic detectors, stalwarts in the analytical chemistry field, are lauded for their precision, wide applicability, and validation in diverse regulatory environments. Terahertz spectroscopy offers unique advantages such as noninvasive testing, profound penetration depth, and bulk sample handling. Meanwhile, Raman spectroscopy stands out with its nondestructive nature, its ability to detect even trace amounts of pesticides, and its minimal requirement for sample preparation. While acknowledging the maturity and robustness of these techniques, our review underscores the importance of persistent innovation. These methodologies' significance extends beyond their present functions, highlighting their adaptability to meet ever‐evolving challenges. Environ Toxicol Chem 2024;43:1468–1484. © 2024 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.


INTRODUCTION
The rising global demand for food security, combined with an emphasis on sustainable agricultural practices, has accentuated the importance of monitoring and managing pesticide residues in food products.Pesticides safeguard crops from pests and diseases, ensuring food abundance.However, the unintended consequence is the potential accumulation of these chemical residues in consumable goods, with ramifications for human health and environmental safety (Li et al., 2023).
The persistence of pesticide residues in the environment and food chain is a matter of concern, primarily because many pesticides have been linked to potential health risks, including endocrine disruption and carcinogenicity (Chen et al., 2021).The environmental impact of pesticides is contingent on various factors, including the type and quantity of pesticides employed, the application techniques, the environmental conditions, and the sensitivity of organisms exposed.Whereas some pesticides are highly toxic and persistent, potentially causing enduring ecological damage, others, although less harmful, can still have adverse effects in specific scenarios.A pesticides classification based on target pest and chemical structure is presented in Figure 1.
To ensure that pesticide residues are not present in food, water, or other environmental samples, it is important to use techniques for pesticide detection that are both sensitive and specific.In recent years, there has been a growing interest in developing new and improved techniques for pesticide detection that are faster, more accurate, and more sensitive.
One promising area of research is the development of biosensors, which use biological molecules such as enzymes or antibodies to detect specific pesticides (Chang et al., 2021;Inam et al., 2022).Another promising area that has gained attention in recent years is nanoparticle-mediated pesticide detection.For example, nanoparticles can function as signal amplifiers, increasing the sensitivity of existing detection methods.They can also be functionalized with specific molecules, such as antibodies or aptamers, to selectively capture and detect target pesticides (Madianos et al., 2018;Yin et al., 2021).A common nanoparticle-mediated pesticide detection method uses spectroscopic techniques such as surface-enhanced Raman scattering (SERS), Fourier transform infrared (FTIR) spectroscopy and terahertz (THz) spectroscopy.These spectroscopic techniques can detect the vibrational signatures of molecules, including pesticides, with high sensitivity.By attaching pesticide-specific molecules to nanoparticles, the SERS, FTIR, and THz signals can be enhanced, allowing for the detection of low concentrations of pesticides (Lee, Oh, et al., 2018;Xu et al., 2023).
Furthermore, chromatographic techniques are widely used in pesticide detection due to their high efficiency in separating the pesticide molecules to be later detected by different techniques, which are characterized by high selectivity and sensitivity (Çakır & Baysal, 2019;Fama et al., 2023;Zhao et al., 2022).Chromatography separates chemical compounds based on their physical and chemical properties, such as their size, polarity, or affinity for certain molecules.Gas chromatography (GC) is commonly used for the analysis of volatile pesticides, which can be vaporized and separated using a GC column.After the division, pesticides are identified with instruments like UV-vis, fluorescence (FLD), ion mobility (IMS), or mass (MS) spectrometers.Liquid chromatography (LC) is used for the analysis of nonvolatile and semivolatile pesticides, which are dissolved in a liquid solvent and separated using an LC column.Several types of LC can be used depending on the properties of the pesticides, such as high-performance liquid chromatography (HPLC), ultrahigh-performance liquid chromatography (UHPLC), or liquid chromatography-mass spectrometry (LC-MS).Chromatographic techniques are widely used in food safety and environmental monitoring, and in pesticide research and development.However, they can be complex and can require specialized equipment and expertise, making them expensive compared with other techniques.
The present review explores the evolution of pesticide detection methods, ranging from traditional to advanced techniques, with a focus on luminescent nanosensors, liquid and GC, THz, and Raman spectroscopies.A comprehensive overview diagram of the methods discussed is presented in Figure 2. The choice of method depends on factors such as the type of pesticide, matrix, sensitivity, selectivity, and costeffectiveness.Each technique offers unique advantages, contributing to the innovation in pesticide residue detection.The subsequent sections delve into the principles, sensitivity, reproducibility, selectivity, advantages, limitations, and applications of each method.Beyond food safety, these advances have far-reaching implications for international trade, economic dynamics, public trust, and environmental conservation.The development of accurate pesticide detection methods has become essential for health, economic stability, diplomacy, and ecosystem protection.

LUMINESCENT NANOSENSORS
Luminescent nanosensors have emerged as promising tools for the sensitive and selective determination of pesticides.Thanks to their broad versatility, these analytical tools offer several advantages, including portability, real-time monitoring capability, the potential for miniaturization, low cost, and simultaneous analysis of multiple analytes (multiplexing).In this section, we discuss the use of luminescent materials to improve pesticide detection, ensuring food safety and environmental monitoring.
As illustrated in Figure 3, nanosensors of this type typically comprise three main components: 1) a luminescent core, 2) a recognition agent, and 3) a luminescence modulation mechanism.The relevance and current state of those elements are summarized in Table 1, and are briefly described using the following selected examples.

Luminescent donors
The most cited works refer to platforms based on carbon quantum dots (CQDs; Su, Li, et al., 2021), chalcogenide quantum dots (Zhou et al., 2018), or metal organic fragments (MOFs; Sohrabi et al., 2022) as luminescent donors.Other nanosensors are also based on coordination polymer nanoparticles (Liu et al., 2022) and upconverting nanomaterials (Su, Zhao, et al., 2021;Yin et al., 2023).The advances in new nanosensors, enabling more sensitive measurements, is closely tied to the design and synthesis of luminescent materials with enhanced emission intensities.In addition, specificity plays a critical role in nanosensors, referring to their ability to selectively detect and respond to specific target analytes amid complex mixtures of other substances.

Recognition elements
The detection of pesticides naturally faces challenges due to the analysis of complex samples and matrices, such as irrigation water, leachates, soils, plants, and their derivatives.To address the lack of selectivity in most nanosensors, various recognition elements have been incorporated, including aptamers, molecular receptors, coordination complex ligands, hydrogen bonding interactions, or specific reactivity.In combination with these components, variations in the intensity, duration, and

Mechanisms for modulating the luminescence
Several mechanisms have been employed to modulate emission intensity, such as resonant energy transfer, reactions catalyzed by natural or artificial enzymes (nanozymes), inner filter effect, control of radiative relaxations of excitons through variations in molecular rigidity, and photo-induced electron transfer (PET).
The proper integration of these elements has allowed the development of new luminescent nanosensors for the detection of pesticides.For instance, MOF-based FLD sensors have been described recently, using the PET as a main mechanism of operation.This process involves the transfer of electrons from the conduction-band (CB) of MOFs to the LUMO of the analytes.When the CB of MOFs is situated at a higher energy level than the LUMOs of the analytes, electron transfer from the ligand to the analytes occurs, leading to the quenching of FLD.For example, a luminescent MOF (ZnPO-MOF) consisting of 1,2,4,5-tetrakis (4-carboxyphenyl) benzene (H4TCPB) with Zn (NO 3 ) 2 •6H 2 O was prepared to detect methyl-parathion with a limit of detection (LOD) of 0.456 mM (Xu et al., 2018).After interaction with this organophosphate, the emission intensity of the system was gradually quenched due to the electron-rich chemical group of nitroaromatics, which might lead to the PET mechanism.A multifunctional FLD sensor based on Eu-MOF was also prepared for detection of antibiotics and pesticides such as dichloro-4-nitroaniline, carbaryl, chlorobenzene, carbendazim, methylparaben, 1,2,4-trichlorobenzene, and bisphenol (Wang et al., 2021).The small pore size of MOFs is harnessed to prevent nonspecific adsorption of molecules on the surface, enhancing specificity.In another representative example, ultrathin MOF nanosheets were decorated with tetra-pyridyl calix[4]arene for glyphosate determination with an LOD of 2.25 μM (Yu, Hu, et al., 2020).In this system, MOF nanosheets exhibited an increment in the backbone rigidity due to the immobilization of glyphosate molecules within the calix[4]arene host, thus facilitating electron transfer.Consequently, nonradiative decay processes were slowed down, leading to an increase in the population of excited species undergoing radiative decay, and thus resulting in a significant FLD enhancement that correlates with the analyte concentration.
Multiple applications have also emerged from the implementation of QDs as donors.For example, a nanoprobe  based on CdTe@CdS QDs, incorporating a guanidiniumcontaining polymer and an aptamer as the recognition component, has been developed for accurately detecting malathion at a low detection limit of 4 pM (Bala et al., 2018).When malathion is not present, the aptamer is bound to the polymer through electrostatic interactions, and thus the FLD of QDs remains unaffected.When present, malathion binds to the aptamer due to its higher affinity than the polymer modulator.As a result, the polymer is accessible to interact with the QDs, leading to the subsequent quenching of the FLD signal.The degree of quenching is directly proportional to the amount of accessible polymer, which, in turn, relies on the concentration of malathion.The herbicide atrazine was also detected using CQDs (Mohapatra et al., 2018).In that study, the NH 3+ in atrazine interacted with ortho-phenylene diamine through hydrogen bonding at acidic pH.The presence of intramolecular motion increases the rates of nonradiative decay, while structural rigidity inhibits this nonemissive pathway, directing the relaxation of excitons through radiative channels.In another aptasensor based on CQDs and gold nanoparticles (AuNPs), the pesticide acetamiprid was detected through a turn-on FLD mechanism based on the inner filter effect (Wang, Xie, et al., 2018).As the insecticide is captured, the quantity of unbound S-18 aptamer sequences diminishes gradually.Therefore, certain AuNPs start aggregating because they are no longer protected by the aptamer, leading to an inadequate quenching of the CQDs' FLD.Consequently, with the continuous addition of acetamiprid, the FLD signals of the aptasensor gradually recover.A LOD of 1.08 μg/L was reached with this strategy.A turn-on fluorescent aptamer-based lateral flow biosensor was coupled to a smartphone spectrum reader for on-site quantification of multipesticides (Figure 4), including chlorpyrifos, diazinon, and malathion, with LOD values of 0.73, 6.7, and 0.74 ng/mL, respectively (Cheng et al., 2018).This approach is based on the use of three biotinylated complementary sequences that are connected to streptavidin.These sequences are then combined with QD-bovine serum albumen conjugates and fixed onto a nitrocellulose membrane, creating three distinct test lines.In the presence of target pesticides, AuNPs-aptamer probes are not captured on the test lines, thus resulting in a FLD signal that becomes visible.When there are no target pesticides present, the AuNPs-aptamer probes are captured on the test lines, resulting in the quenching of FLD.The CQDs have also been combined with nanozymes for organophosphate pesticide detection.Nanozymes are a collective assembly that combines the catalytic properties of enzymes with the characteristics of nanoscale materials.In contrast to natural enzymes, these nanozymes possess enhanced stability and can be mass-produced at a reduced cost.As a result, they have found extensive use in the detection of pesticides and other pollutants.They have been proved to possess peroxidaselike, catalase-like, oxidase-like, and superoxide dismutase-like activities (Li et al., 2019).A turn-on enzymatic biosensor based on CQDs was prepared for organophosphate pesticide detection up to 0.778 μM (Sahub et al., 2018).In this concept, the H 2 O 2 generated from the enzymatic reaction of acetylcholinesterase and choline oxidase reacts with CQDs, attenuating its FLD.The emission intensity is then recovered in the presence of organophosphate molecules such as dichlorvos, malathion, methyl-parathion, and ethyl parathion.
Despite these advances, the current detection of pesticides still faces several challenges, including low selectivity, physicochemical instability, low reproducibility, and technical complexity.Metal ions present in soil and water can interfere with pesticide detection, and current techniques have limitations in providing specific recognition elements and responsive signal readouts for real-time monitoring at the location of interest.Moreover, pesticides have varying environmental half-lives, leading to fluctuations in the analytical response.Furthermore, the optoelectronic properties, long-term stability, and durability of most luminescent materials heavily depend on ambient environmental factors.This dependence can hinder their reliable performance.Research is ongoing to develop new materials and methods that can offer better specificity and stability, as well as portable and visible testing for rapid and convenient detection of these pollutants.Therefore, more efforts should be made to develop and implement nanosensors for a comprehensive comparison of their sensing performance on a larger scale.

CHROMATOGRAPHY
Chromatography is a widely used technique for isolating pesticide molecules from various samples, including food, water, soil, and air, enabling their detection through different methods (Figure 5).This method relies on the distribution of components between a mobile and a stationary phase for separation.The rate at which the band migrates depends on the mobile phase.In column chromatography, the stationary phase commonly consists of a fine adsorbent solid capable of retaining gas or liquid particles on its outer surface.The choice of absorbent material in the stationary phase and the selection of an appropriate mobile phase play crucial roles in achieving efficient separation.
Chromatography can be classified based on the types of mobile and stationary phases and the kinds of equilibria involved in the transfer of solutes between phases.There are three broad categories: LC, GC, and supercritical-fluid chromatography (SFC), which rely on different mobile phases.Table 2 briefly describes some examples of the application of those techniques for separation and detection of pesticides.Compared with LC and GC, which are more established, SFC is a less common method for pesticide detection.For this reason, and due to its limited use in this context, SFC is not covered in our review.

Liquid chromatography
Liquid chromatography utilizes a liquid mobile and a stationary phase, typically a solid material, or a liquid immobilized on a solid support within a column.The separation is based on the varying affinities of analytes for the stationary and mobile phases.In the process, the sample is carried through the column by the mobile phase, and as it interacts with the stationary phase, components with different affinities experience distinct levels of retention and elution.Detection and quantification of separated components can be achieved using various detectors like UV-vis, FLD, IMS, or MS spectrometers.
Numerous studies have been dedicated to advancing LC techniques for pesticide detection, focusing on improving sensitivity, selectivity, and overall performance.These enhancements encompass not only the chromatographic separation and detection processes but also extend to sample preparation and extraction techniques.By refining sample preparation and extraction methodologies, researchers have successfully tackled challenges associated with complex matrices and trace amounts of target analytes, enhancing the effectiveness of LC-based pesticide detection.
For instance, researchers have introduced an innovative method combining HPLC-UV detection, microwave-assisted extraction (MAE), and ultrasonic-assisted dispersive liquid-liquid microextraction (UADLLME) for simultaneous determination of pyrethroid residues in Litchi fruit (Wang, Xie, et al., 2018).In the MAE process, 0.5 g of either the outer skin (pericarp) or the dried inner section (pulp) is mixed with 20 mL of ethanol and extracted using a microwave extraction system at 70 °C and 780 W, for a span of 4 min.After cooling, the solutions are filtered to obtain the purified extract.In the UADLLME process, a mixture is prepared by combining 1.3 mL of filtrates with 5 mL of deionized water followed by the addition of 310 μL of chlorobenzene as the extraction solvent.The mixture is separated by ultrasonic waves, followed by centrifugation.The denser phase is then dry by evaporation and reconstituted in 100 μL of methanol for HPLC analysis.The optimized method has exhibited a wide linear range (0.0050-4.98 mg/L), high recovery rates (83.3-91.5%),low relative standard deviations (RSDs) below 5.6%, and low detection limits (1.15-2.46μg/L) for six pyrethroids.The combination of MAE and UADLLME provided improved extraction efficiency and larger enrichment factors, making it a sensitive and efficient alternative for detecting trace pesticide residues in food samples.This method has the potential for use as a sample preparation technique in real-world scenarios.
The development of innovative extraction methods is pivotal in enhancing the efficiency and accuracy of LC techniques.Heidari et al. (2020) introduced a novel approach called deep eutectic solvent-based ultrasound-assisted liquid-liquid microextraction (DES-UALLME) for determining organophosphorus pesticides (phosalone and chlorpyrifos) in fruit juice samples using the HPLC-UV technique.The optimized conditions yielded low detection limits (0.070 and 0.096 ng/mL), high enrichment factors, and good extraction recoveries.The method was successfully applied to analyze phosalone and chlorpyrifos in red grape juice and sour cherry juice samples, with satisfactory relative recoveries.Three distinct types of DES were prepared, including ChCl with urea, ethylene glycol, and Ph.The study highlights the potential of DES-UALLME as a simple, cost-effective, and efficient technique for the extraction and analysis of organophosphorus pesticides in fruit juice samples.
Detecting pesticide residues in vegetables is challenging due to the limited number of target analytes and the complex FIGURE 5: Principle of separation in chromatography techniques: At time t 0 , the mixture of components A + B sits atop the column.The determination of the relative polarities of these two compounds relies on the polarities of both the stationary and the mobile phases.Over time, there will be different interactions between the two components A and B that will cause a separation of these components into discrete bands.interferences present in vegetable matrices.To address these obstacles, researchers developed the quick, easy, cheap, effective, rugged, and safe (QuEChERS) approach, which has gained attention for its simplicity, speed, and effectiveness.This method involves the use of acetonitrile for extraction and dispersive solid-phase extraction (d-SPE) for purification (Camara et al., 2017).The QuEChERS method has been widely used to extract pesticides from both plant and animal matrices, and it has been officially recognized as a method for determining pesticide residues in vegetables.However, the limited enrichment factor of QuEChERS restricts its sensitivity, requiring further improvement (Mao et al., 2020).
One such alternative is dispersive liquid-liquid microextraction (DLLME), known for its high enrichment factor, rapid extraction speed, and minimal reagent consumption.It is commonly used for pesticide extraction in aqueous samples, and its application to solid food samples remains a challenge.Mao et al. (2020) provided calibration curves that exhibit satisfactory linearity (R 2 ≥ 0.99) when analysis is performed in matrix-matched standard solutions.The method achieved low limits of detection (0.3-1.5 μg/kg) and limits of quantification (0.9-4.7 μg/kg).Moreover, the effectiveness and reliability of the developed method were validated through its successful application in analyzing pesticide levels in 15 pairs of organic and conventional vegetables.Yu, Hao, et al. (2020) focused on the analysis of trace substances, specifically organophosphorus pesticide residues, in tea.The authors addressed the challenges posed by strong matrix effects caused by tea polyphenols, chlorophyll, and lutein, which make the analysis of trace substances difficult.They proposed a targeted strategy using modified QuEChERS sample preparation coupled with HPLC-tandem mass spectrometry (MS/MS) detection.They first investigated the removal ability of seven different adsorbents (graphitized carbon black, C18, pressure swing adsorption, multiwalled carbon nanotubes [MWCNTs], MWCNTs-COOH, MWCNTs-OH, and MWCNTs-NH 2 ) for tea polyphenols, chlorophyll, and lutein through adsorption isotherm fitting, and found that MWCNTs-NH 2 GC-MS = gas chromatography-mass spectrometry; GC-IMS = GC-ion mobility spectrometry; HPLC-UV = high-performance liquid chromatography-UV; GC-μECD/ NPD = GC-microelectron capture and nitrogen-phosphorus detection.
demonstrated the strongest removal ability, potentially due to π-π and electrostatic interactions.Based on this finding, they developed and validated a method using MWCNTs-NH 2 modified QuEChERS for the detection of 10 organophosphorus pesticide residues in tea.This method simplifies the sample preparation by replacing the combination of various adsorbents with a single adsorbent, improving the ease and generality of the method.The method is validated through various parameters, including linearity, matrix effect, accuracy, precision, LOD, and limit of quantification, following the SANTE/11813/2017 guidelines (European Commission, 2017).

Gas chromatography
Gas chromatography is a method for analyzing samples that can be vaporized without undergoing thermal decomposition.Also referred to as vapor phase chromatography or gas-liquid partition chromatography, the latter is the most accurate term for the technique, which relies on the interaction between a flowing mobile gas phase and a stationary liquid phase to separate and analyze the components (Daviau, 2004).In the process, the sample is dissolved in a compatible solvent, typically in microliter quantities, and introduced as a liquid mixture into the gas chromatograph.After evaporation, an inert gas like argon, nitrogen, or hydrogen carries the sample through a long tube, where components are separated based on molecular weights, polarizability, and boiling points.The detector placed at the tube's end records the sample amount that reaches it.The unique transit time for each component along the tube allows their identification (Broekaert, 2015).Gas chromatography is particularly effective for identifying components of a liquid mixture and determining their concentrations down to the picogram range, depending on the detector used.Even though GC is a complete analysis technique on its own, it is commonly employed in conjunction with MS for a more comprehensive analysis of the chemical composition of the sample.
Several studies have been conducted to evaluate the suitability of this technique for pesticide detection and, consequently, several improvements to the technique have also been proposed, with the aim of make it more accurate, simple, and able to assess a wider range of pesticides.The improvements achieved are not limited to the chromograph components and performance itself but also to the sample pretreatment, solvents and carrying gases used.
For instance, Taghani et al. (2018) have introduced a novel, low-cost method employing microextraction in packed syringe (MEPS) coupled with GC-MS, targeting the preconcentration and determination of diazinon, ethion, and malathion.A key highlight of that study is the use of natural nanoperlite as a sorbent.The technique involves adsorbing the analytes onto the nanoperlite packed in a syringe, followed by elution using a desorbing solvent.The method displays a commendable linear range and low detection limits, showcasing its efficacy in detecting these pesticides at trace levels.The preparation of the MEPS device, utilizing a simple glass insulin injection syringe packed with nanoperlite, underpins the method's simplicity and accessibility.The extraction procedure, including conditioning, washing, and extraction steps, is meticulously detailed, ensuring the elimination of interferences and effective preconcentration of the pesticides.The final desorption and GC-MS analysis allow for precise and sensitive detection of the target organophosphorus pesticides.
Chen and Xu (2019) proposed an innovative approach for detecting pesticide residues in garlic.The study focused on the development and application of a customized multiwalled carbon nanotubes/polybiline-polyrrole@polydimethylsiloxane (MWCNTs/PANI-PPy@PDMS) fiber for in vivo solid-phase microextraction (SPME), combined with GC-MS.The custommade fiber demonstrates superior enrichment capacity compared with commercially available SPME fibers, exhibiting high enrichment factors, thermal and mechanical stability, and excellent matrix compatibility.This robust fiber effectively overcomes common analytical challenges such as biofouling, making it highly suitable for in vivo sampling of edible plants.The method developed, employing in vivo SPME-GC-MS, provides a rapid, sensitive, and efficient means for detecting various pesticides, including hexachlorobenzene, chlorothalonil, fipronil, and chlorfenapyr, in garlic samples.
Continuing the exploration of advanced techniques for detecting organophosphorus pesticides, the study conducted by Jafari et al. (2018) involved the use of carbon-silica hybrid nanofibers, serving as a high-performance coating for SPME fibers, in combination with GC-corona discharge ion mobility spectrometry (GC-IMS) for pesticide analysis In this technique, the carbon-silica hybrid nanofibers are synthesized through a sol-gel electrospinning process using polyacrylonitrile (PAN) and tetraethyl orthosilicate (TEOS) as carbon and silica precursors, respectively.The introduction of TEOS into the PAN solution, resulting in increased surface area, significantly enhances the extraction performance of the hybrid nanofibers compared with commercial fibers and bare PAN nanofibers.The use of GC-IMS as a hyphenated technique for the separation and determination of organophosphorus pesticides in aqueous solutions adds another layer of efficiency to the method.
In addition, Słowik-Borowiec and Szpyrka (2018) have identified and quantified over 131 pesticides in wine and grapes.Their method is a significant advancement from the earlier discussed carbon-silica hybrid nanofibers for SPME and demonstrates the versatility of GC techniques in handling complex matrices like food and beverages.The research focused on two extraction methods: QuEChERS citrate buffer and unbuffered methods.Their study undertook a through validation of these analytical methods, considering various clean-up strategies to optimize the extraction and detection of pesticides.The GC with microelectron capture and nitrogenphosphorus detection (GC-µECD/NPD) proved to be an effective, cost-efficient alternative to more expensive mass spectrometry techniques.Their study not only enhanced the analytical capabilities for pesticide residue detection in wine and grapes but also showed the potential of GC-µECD/NPD as a practical alternative for routine monitoring of pesticide residues.Also, its effectiveness, accuracy, and reproducibility, coupled with the cost and time savings, make this developed method ideal for regular monitoring applications.
On the other hand, the advent of innovative microextraction techniques has revolutionized our ability to detect and quantify these compounds in various samples with enhanced efficiency and scope.For instance, in the study conducted by Szarka et al. (2018), the authors used DLLME coupled with GC-MS.This method stands out for its economical and rapid detection of 40 different pesticides in nutraceutical drops containing alcohol.By optimizing several key parameters, the study achieved low limits of detection, high extraction recoveries, and satisfactory linearity.In contrast, Tazarv et al. (2021) presented an environmentally sustainable bursting-bubble flow microextraction (BBFME) method, combined with GC, that effectively analyzes organophosphorus pesticide residues in water samples.With its low solvent consumption and high extraction efficiency, BBFME represents a significant advance in green analytical methods, aligning with environmental safety goals.
Chromatographic techniques, encompassing both liquid and gas methodologies, remain crucial in pesticide detection, ensuring environmental and food safety.The ability of LC to analyze polar compounds complements GC's ability to assess volatile pesticides, offering a comprehensive detection spectrum.With global food safety concerns on the rise, researchers are innovating these techniques, integrating advanced detectors and multiresidue methods for more efficient analyses.The fusion of chromatography with emerging technologies promises enhanced detection capabilities, aiming for a more thorough safeguard against the potential hazards of pesticide residues in the future.

TERAHERTZ SPECTROSCOPY
Over the years, THz radiation has emerged as a promising, nondestructive technique for pesticide detection, positioned between microwaves and infrared light.Its unique ability to probe molecular and structural dynamics makes it well suited for detecting minute traces of pesticides.However, the disparity between THz wavelengths and the size of targeted molecules, compromises sensitivity.In the realm of THz technology, diverse methodologies have emerged to enhance pesticide detection using THz radiation.These approaches encompass: 1) development of metamaterials, 2) utilization of computational techniques for signal processing, and 3) THz spectral imaging technology.These strategies collectively aim to augment the sensitivity, precision, and overall efficacy of THz-based pesticide detection methods, as summarized in Table 3.

Enhancing sensitivity with metamaterials
The most referenced studies in the field are those that have pioneered the development of metamaterials.For instance, Qin et al. (2018) have presented an innovative method to detect carbendazim in liquid samples at different concentrations (0, 0.5, 5, 20, 50, 100, and 300 mg/L).This pioneering method employs THz time-domain spectroscopy (THz-TDS) in conjunction with metamaterials.The metamaterial is elegantly straightforward, featuring metal ohm ring arrays.Fabrication involves a surface where a photoresist layer shapes the ohm ring arrays.After exposure to ultraviolet light and subsequent development, these array patterns are etched onto a highresistance silicon substrate.An aluminum layer is then applied and, metal ohm ring arrays are defined using a liftoff process with a 74-μm cycle.The silicon substrate has a thickness of 350 μm, and the aluminum ohm ring measures 0.1 μm in thickness.
This metamaterial exhibits sensitivity to changes in the relative permittivity of the contacting solution.Variations in the solution's relative permittivity induce corresponding shifts in the resonant peak positions of the metamaterial.Notably, the liquid samples containing carbendazim and anhydrous alcohol boast high purity levels of 98% and 99%, respectively, minimizing contaminants.Consequently, the metamaterial demonstrates exceptional precision in pinpointing minute quantities of carbendazim, because alterations in relative permittivity directly correlate with changes in carbendazim concentration.This ground-breaking methodology holds significant promise for accurate and sensitive pesticide detection in liquid samples.
In an analogous manner, Wang, Zhu, et al. (2020) innovatively explored a THz metasurface absorber approach using dielectric resonators crafted from heavily doped silicon.They introduced a simplified fabrication structure, emphasizing single-patterned designs via conventional photolithography and deep reactiveion etching.The resulting all-dielectric metasurface THz absorbers (AMTA) on an n-type doped silicon wafer exhibited absorption rates reaching 99.8% at 1.44 THz.Notably, AMTA demonstrated sensitivity to refractive indices, successfully detecting the pesticide 2,4-dichlorophenoxyacetic acid (2,4-D) in concentrations from 0.05 to 4 ppm.Its potential in biochemical and environmental monitoring was underscored, showcasing its versatility.
Expanding on THz radiation and metamaterials' potential in pesticide detection, Xu et al. (2020) introduced a groundbreaking metamaterial-free, graphene-based THz sensor with user-designed patterns for bio-interface sensing.Leveraging graphene's unique properties, external molecules interacted strongly, with its electrons causing a shift in the Fermi level and altering THz absorption.The sensor detected chlorpyrifos methyl with a commendable LOD at 0.13 mg/L, showcasing the method's adaptability and consistency in real-world scenarios.The flexible graphene THz sensor demonstrated durability over 1000 bending cycles, emphasizing its manifold advantages in environmental monitoring.
In a significant advancement, Wang, Cui, et al. (2020) explored plasmonic metasurfaces using carbon nanotubes (CNTs) for discerning pesticide levels.The sensor, created from highly aligned multiwalled CNTs, utilized CNT's metal-like conductivity to form a subwavelength periodic structure.The resulting plasmonic metasurface sensors (PMSs) effectively detected varying concentrations of 2,4-D and chlorpyrifos solutions, showcasing their potential for differentiating pesticide concentrations.The reliability and consistency of these PMSs highlighted their suitability for real-world sample testing.

Computational techniques for signal processing
Transitioning from the exploration of metamaterial approaches for pesticide detection, our focus now shifts to research emphasizing THz spectral analysis.For instance, Qu et al. (2018) analyzed the spectral properties of three permethrin pesticides (deltamethrin, fenvalerate, and beta-cypermethrin), using THz-TDS.They employed the wavelet threshold denoising technique to address instrument inaccuracies in the THz spectrum, incorporating the spectral baseline correction approach to tackle baseline drift due to high-frequency absorption.Additionally, density functional theory (DFT) was utilized to study molecular behavior and vibration patterns.Experimentally derived absorption peaks were matched with theoretical computations, and the linear addition technique simulated THz spectra for pesticide combinations.The study aimed to enhance spectra quality and analysis precision, shedding light on the detection process, and providing insights for THz-TDS-based spectral examination of pesticide blends.
Expanding on the use of DFT, Nie et al. (2019) applied it for geometry optimization and vibrational frequency calculations of 2,4-D, using THz-TDS to quantitatively detect 2,4-D in Zizania latifolia.Three absorption peaks at 1.36, 1.60, and 2.38 THz were identified, with the 1.36-THz peak serving as a primary indicator for quantitative analysis.The study demonstrated THz-TDS potential in quantifying 2,4-D in Zizania latifolia, with a detection threshold below 5%, and a strong linear correlation between 2,4-D concentration and absorbance.This research contributes to the THz spectroscopy database for pesticide molecular identification and offers a method for detecting 2,4-D in food via THz spectroscopy.However, there is an opportunity to refine the detection limit by enhancing the instrument's capabilities and introducing effective signal boosters in subsequent studies.

THz spectral imaging technology
Shifting the focus to recent advances in THz spectral imaging technology and its role in examining agricultural products for pesticide residues, we highlight the emerging role of machine learning methodologies, exemplified by Ge et al. (2021) and Lee et al. (2016).Although most agricultural products scanned with THz waves exhibit absorption peaks, certain substances, especially mixtures, may lack clear absorption peaks, complicating straightforward analysis.To address this, deep learning algorithms, such as convolutional neural networks and deep belief networks have been introduced to dissect spectral attributes, facilitate feature extraction, and enhance the resolution of THz imaging.In a study by Nie et al. (2021), THz imaging combined with deep learning was explored for the quick and simultaneous detection of minute benzimidazole residues on Toona sinensis leaves.The experiment involved extracting the THz spectra from tested leaves exposed to individual or combined components of benzoyl (BNL), carbendazim (BCM), and thiabendazole (TBZ) at a concentration of 10 mg/L.The study aimed to identify THz signature peaks of BNL, BCM, and TBZ, and simulate their molecular movements using solid DFT, classifying trace residues on leaves using these signature peaks and swiftly pinpointing these residues on leaves using a deep convolution neural network.The findings indicate that the technique merging THz imaging and deep learning is highly effective for analyzing minute pesticide residues on T. sinensis leaves, with potential applications in routinely monitoring pesticides in other leafy vegetables, thereby promoting food safety.
Terahertz spectroscopy has emerged as a cutting-edge solution for pesticide detection, addressing the evolving challenges in food safety.Uniquely positioned in the electromagnetic spectrum, THz radiation provides sensitive and nondestructive insights into molecular dynamics, especially when combined with advanced materials like metamaterials, graphene, and carbon nanotubes.This synergy enhances detection sensitivity, pushing the boundaries in identifying minute pesticide residues.The integration of computational methodologies, such as DFT with THz-TDS, contributes to a deeper understanding of molecular behaviors, facilitating accurate and precise contaminant detection.The future looks promising for THz imaging technology seamlessly integrating with machine learning methodologies, promising new dimensions in pesticide residue analysis.The ongoing research underscores the pivotal role of THz spectroscopy in revolutionizing environmental integrity and ensuring the safety of global food chains.

RAMAN SPECTROSCOPY
Raman spectroscopy, a nondestructive and powerful analytical technique, allows the identification of molecules by their specific vibrational signatures.Despite its widespread use, Raman spectroscopy faces limitations, especially low Raman scattering.This drawback manifests in weak Raman signals, especially for samples with poor dispersion or low molecular mass.These complications can reduce the sensitivity of the method, requiring longer acquisition times or higher laser powers for accurate analysis.
The scientific community has widely agreed on the profound significance of SERS as a pioneering technique that surpasses the limits of sensitivity, allowing for the detection of single molecules.This achievement is attributed to the interplay of two key mechanisms; the first is associated with electromagnetic (EM) enhancement resulting from localized surface plasmon resonance (LSPR), and the second is related to electron transfer between the molecule and the substrates, which is known as chemical enhancement.
The process's cost-effectiveness, ease of synthesis, and tunable plasmonic resonance, ranging from UV to near infrared, make gold and silver nanoparticles the preferred choice for SERS applications.This advance is particularly significant in the realm of pesticide detection, offering a highly sensitive and precise method to analyze samples and ensure environmental and food safety (Table 4).
4-Aminothiophenol (4-ATP) is considered a highly toxic pesticide intermediate that can be readily absorbed by the human body, Some studies have suggested that this compound leads to protein denaturation and immune diseases, making it crucial to identify its presence accurately.In a study conducted by Lee, Oh, et al. (2018), it was demonstrated that a functionalized filter paper, combined with silver nanoparticles (AgNPs), can serve as an effective SERS substrate for detecting 4-ATP.The filter paper was modified with alkyl ketene dimer to enhance its hydrophobic properties, ensuring the retention of silver NPs on its surface.The Raman results revealed that the 1073-cm −1 band of 4-ATP exhibited a significant correlation with the quantity of AgNPs present on the cellulose substrate.Through Raman spectra analysis and discrete dipole approximation simulations, it was determined that the optimal concentration of the AgNP solution was 1.5 nM, corresponding to the formation of a two-layer structure of AgNPs on the filter paper surface.The sensor shows relatively high reproducibility along the different examined spots of the substrate, with limits of detection of approximately 0.45 nM after the interaction with thiram and ferbam pesticides as sensing targets.Polyhedral AuNSs have proved to be a highly effective metallic-based SERS platform for detecting 4-ATP, exhibiting an important analytical enhancement factor at the 1076-and 1583-cm −1 Raman bands (Sun et al., 2019).
Another commonly used pesticide to control broadleaf weeds is 2,4-D, exposure to which can lead to skin and respiratory issues, while environmental concerns include contamination of water sources and harm to aquatic life.Some strategies using SERS have been developed to detect this pesticide.For example, devices utilizing metallic electrode arrays containing a blend of gum arabic and AuNPs as the SERS active layer, have been exploited to detect the herbicide 2,4-D herbicide in diverse matrices such as mineral or river water (Yang et al., 2022).By normalizing the intensity ratios of the 293-and 1130-cm −1 bands with the 1400-cm −1 band, the detection range spans from 0.15 nm to 1.5 µM.The work of Xu et al. (2020) shows that 2,4-D can also be detected in more complex matrixes such milk or tea using antibody-functionalized magnetite nanoparticles (antibody-MNPs) as an enrichment probe and antigen-multiple banded antigen-functionalized hollow Au@Ag bimetallic nanoflowers.
Efficient detection of organophosphates is crucial for ensuring food safety.Raman spectroscopy and its enhanced form, SERS, have emerged as techniques for identifying these pesticide compounds with high sensitivity.Lee, Liao, et al. (2018), exploited the unique properties of zirconia nanofibers (ZrO 2 NFs) crafted via a spin-coated sol-gel method, and then optimally adorned with AuNPs.This composite, AuNPs/ZrO 2 NFs, serves as an innovative SERS-active substrate, leveraging the structural benefits of nanofibers to enhance the surface area and the SERS effect of AuNPs for heightened sensitivity.
Their study demonstrates the substrate's impressive capability to detect various organophosphates: phosmet, carbaryl, permethrin, and cypermethrin, at concentrations as low as 10 −8 -10 −6 M.These researchers went further to test the practical application of this method, using apple peels contaminated with pesticides.The diluted juice containing these peels revealed clear identification of each pesticide.
In pursuit of efficient detection methods, Feis et al. ( 2020) delved into the detection of glyphosate, a widely used organophosphate herbicide whose presence in the environment has raised significant concerns.Their the study harnessed SERS spectroscopy, employing AgNPs as a substrate, to detect glyphosate and its related compounds.The uniqueness of their study lies in its comparative approach.By analyzing SERS spectra of glyphosate and its isotopically substituted derivative (13C-glyphosate), alongside aminomethylphosphonic acid (AMPA), the researchers could unravel the complexities of glyphosate's vibrational spectra.The use of AMPA in the study is noteworthy, because it not only relates structurally to glyphosate but also holds its toxicological significance.A key finding is the deviation of glyphosate's SERS spectra from its standard Raman and infrared spectra when absorbed onto dispersed AgNPs.The study successfully assigned the bands in the experimental SERS spectra, with isotopic substitution providing insights into the molecular orientation and absorption effects on the AgNPs.By ruling out AMPA's contribution to the SERS spectra under experimental conditions and focusing on the adsorption dynamics of glyphosate on AgNPs, the study paves the way for a deeper understanding of glyphosate's  2022) took a significant leap forward in the field.This research introduced a novel SERS substrate that combines the unique properties of reduced graphene oxide (rGO), AgNPs, and titanium dioxide nanotubes (TiO 2 NTs).The composite structure TiO 2 NTs/AgNPs-rGO exhibits exceptional sensitivity and stability, making it a potent tool for directly detecting glyphosate in the environmental samples.
The vertically aligned TiO 2 NTs, grown on titanium sheets through electrochemical anodization, serve as a robust backbone for this sensor.The dual-layer AgNPs, uniformly deposited onto the TiO 2 NTs, amplify the electromagnetic field, creating an abundance of SERS hot-spots.The rGO wrapping not only enhances stability but also selectively binds to glyphosate, facilitating its direct detection, a significant advance over previous methods that required indirect or complex pathways for glyphosate sensing.
In the realm of organophosphate pesticide detection, particularly focusing on malathion, Aheto et al. (2023) have introduced a novel method for its detection.The detection malathion, known for its detrimental effects on the central nervous system in humans and animals, calls for effective strategies, and their study contributes significantly in this regard, using SERS.The innovation in their study lies in the fabrication of a unique SERS active substrate, named AC@AgNPs, which conjugate activated carbon (AC), trapping AgNPs.Quantitative analysis of malathion using this SERS substrate was achieved through regression models, particularly using the standard normal variate-partial least squares regression approach, which showed remarkable performance, with a correlation coefficient of 0.9869 and a residual predictive deviation of 4.61.Zhai et al. (2022) have complemented the previous study on malathion detection by introducing a flexible SERS substrate, prepared with AgNPs-polydimethylsiloxane (PDMS), for rapid and on-site detection of pesticide residues.The AgNPs-PDMS substrate, characterized by a relative standard deviation of 5.33% and stability up to 30 days, demonstrated remarkable sensitivity in detecting pesticide residues on orange surfaces.Crucially, it established a linear relationship between the characteristics SERS bands and the concentrations of the target pesticides, achieving detection limits as low as 3.62 µg/L for thiram, 41.46 µg/for malathion, and 15.69 µg/L for phoxim.
The integration of SERS with various substrates and nanostructures, as demonstrated in previous research, has significantly pushed the boundaries of pesticide detection.From optimizing signal stability and enhancing detection limits, to introducing practical applications such as swabbing tests and portable detection systems, these studies collectively present a promising trajectory for the future of pesticide detection methodologies.
Metallic nanostructures have proved effective as SERS substrates for pesticide detection, but they come with certain drawbacks.For instance, energy dissipation during analysis may damage samples, especially at low analyte concentrations (Ioffe et al., 2008).In addition, the large surface area-to-volume ratio of metallic nanoparticles can lead to corrosion and oxidation, impacting result reproducibility (Kang et al., 2019).Moreover, preventing undesirable particle aggregation requires additional processing steps.

DISCUSSION
The pursuit of global food safety has prompted the development of sophisticated pesticide detection methods, each tailored to meet the rigorous demands of accuracy, efficiency, and reliability.Leading this innovation are cutting-edge technologies, each with its unique strengths and capabilities.
Luminescent nanosensors have revolutionized pesticide detection by offering unparalleled sensitivity and specificity.The synthesis of new luminescent materials has significantly enhanced detection capabilities, even at ultra-low pesticide concentrations, hinting at a future in which real-time, on-site analysis becomes routine.However, challenges such as selectivity and physicochemical stability persist, underscoring the need for continued research and development.
Chromatography, both liquid and gas, remains a mainstay in the realm of pesticide detection, underscored by its enduring utilization and continuous advances.These techniques excel through sophisticated separation mechanisms, which have been continuously refined to enhance sensitivity and selectivity.Acknowledged for high separation efficiency and resolution, they are suitable for a wide range of compounds, from volatile to nonvolatile substances.Notably, LC has advanced in analyzing polar compounds, whereas GC excels in volatile substance analysis, particularly when coupled with mass spectrometry.However, meticulous sample preparation and processing are required, demanding significant time and technical expertise.Additionally, the cost of the instruments and environmental reagents used in sample preparation may pose challenges.Despite these drawbacks, chromatography techniques share the common goal of improving pesticide analysis efficiency and accuracy.Recent innovations, including advanced detectors and multiresidue methods, address global concerns over food safety, representing significant leaps forward toward comprehensive monitoring of pesticide residues.By continuously pushing the analytical boundaries, chromatography remains pivotal in ensuring food safety and integrity.
Terahertz spectroscopy, emerging as a noninvasive detection method, represents a significant advance in the field of pesticide detection.By harnessing the unique properties of THz waves, this technique unveils molecular fingerprints of contaminants with remarkable precision and sensitivity.The integration of THz spectroscopy with advanced materials and computational techniques has pushed its capabilities to new heights, offering not only sensitive analysis but also spectral imaging of pesticides in diverse matrices.Metamaterials, graphene, and CNTs are among the advanced materials that have revolutionized THz spectroscopy, enhancing its ability to detect pesticides at concentrations previously unattainable with conventional methods.Furthermore, computational techniques such as machine learning algorithms have been seamlessly integrated into THz spectroscopy, enabling automated, highthroughput analyses that could revolutionize the field of pesticide detection.The research presented in this review underscores the tremendous potential of THz spectroscopy as a versatile and powerful tool for nondestructive analysis of pesticide residues in food and environmental samples.With continuous advances and innovations, THz spectroscopy is poised to play a pivotal role in ensuring the safety and integrity of our global food supply.
Raman spectroscopy, especially when coupled with SERS, stands out as a powerful tool for rapid and sensitive detection of pesticides.Despite its strengths, Raman spectroscopy encounters challenges related to sample degradation and reproducibility, stemming largely from the limitations of metallic nanostructures used in conventional SERS substrates.However, recent advances in semiconductor-based SERS substrates offer a promising solution to these obstacles.Semiconductor materials such as TiO 2 , ZrO 2 , and SiO 2 provide a broader spectrum of electromagnetic enhancement compared with metallic nanoparticles, thereby enhancing sensitivity and signal stability.Moreover, precise control over the physical of semiconductor materials allows for tailored substrate engineering, addressing issues of reproducibility and longevity.Surface functionalization strategies further augment the selectivity of semiconductor-based SERS substrates, enabling targeted detection of specific pesticides amid complex matrices.By leveraging these advances, Raman spectroscopy is poised to overcome its limitations and emerge as a robust and reliable technique for pesticide detection in food and environmental samples.As research in this field continues to evolve, the integration of semiconductor-based SERS substrates with advanced analytical methods promises to further enhance the efficacy and applicability of Raman spectroscopy in ensuring food safety and environmental sustainability.
Even as we assimilate these findings, challenges linger.The scalability and adaptability of these techniques across different agricultural matrices, their economic feasibility, and the evolving nature of global pesticides necessitate continuous innovation.Furthermore, the integration of computational techniques like machine learning can significantly enhance the interpretative capabilities of these methodologies.Our pursuit of impeccable food safety through advanced pesticide detection has been marked by significant milestones, yet the journey continues.As we integrate, adapt, and innovate, the overarching goal remains steadfast: to vouchsafe the integrity of our global food systems and the environment that nurtures them.

CONCLUSIONS
Our review has systematically assessed the current state of pesticide detection technologies, scrutinizing their applicability within the domain of food safety.The enhanced sensitivity of luminescent nanosensors, the well-established robustness of chromatographic methods, and the burgeoning promise of THz and Raman spectroscopy have each been critically evaluated.These methods have been instrumental in forming the bulwark of our analytical capabilities, ensuring the integrity of global food systems.
Notwithstanding their significant contributions, it is evident that these technologies are not without limitations.The dynamic nature of pesticide compounds, the increasing complexity of food matrices, and the evolving exigencies of global supply chains necessitate ongoing advances in our detection methodologies.The instruments at our disposal have demonstrated considerable efficacy, yet the imperative remains to push the frontiers of these methods further, refining and augmenting them to meet and surmount emerging challenges.Hence there is a clear mandate for continuous methodological innovation and the pursuit of synergistic approaches in pesticide detection.The combination of computational tools with conventional detection strategies offers a particularly fertile ground for advancement.Leveraging machine learning algorithms and artificial intelligence can potentially transform data interpretation, facilitating more nuanced and rapid decisionmaking processes in food safety assessment.
The future trajectory of pesticide detection, as this review posits, must be aligned with proactive adaptation and anticipation of future requirements.As the scientific community endeavors to publish findings that will serve as harbingers of the next generation of advancements, the shared objective remains unequivocal: to refine and innovate on our detection methodologies to ensure they are not merely adequate but exemplary, thereby fortifying the safety of our food and the health of populations worldwide.In striving toward this goal, we acknowledge the progress made thus far while recognizing the journey ahead is both vital and ongoing.
Data Availability Statement-The authors confirm that this review article does not include any Supporting Information.All data and information essential for understanding and evaluating the content of this manuscript are presented within the main text and references.Therefore, there are no additional datasets, files, or other supplementary materials to be made accessible.We are committed to transparency and accessibility in research and affirm that all pertinent information is available in the published article.

FIGURE 2 :
FIGURE 2: Comprehensive overview diagram of the methods discussed.

TABLE 1 :
Luminescent nanosensors for pesticide detection, and related parameters

TABLE 2 :
Performance of gas-and liquid-based chromatographic techniques used for separation and detection of pesticides

TABLE 3 :
Overview of terahertz spectroscopy techniques in pesticide detection

TABLE 4 :
Surface-enhanced Raman scattering platforms used for detecting various pesticides, with their key findings