Investigation of Pesticide Penetration and Persistence on Harvested and Live Basil Leaves Using Surface-Enhanced Raman Scattering Mapping

Surface-Enhanced Raman Scattering Imaging Assisted by Machine Learning Analysis: Unveiling Pesticide Molecule Permeation in Crop Tissues

Surface-enhanced Raman scattering (SERS) imaging technology faces significant technical bottlenecks in ensuring balanced spatial resolution, preventing image bias induced by substrate heterogeneity, accurate quantitative analysis, and substrate preparation that enhances Raman signal strength on a global scale. To systematically solve these problems, artificial intelligence techniques are applied to analyze the signals of pesticides based on 3D and dynamic SERS imaging. Utilizing perovskite/silver nanoparticles composites (CaTiO3/Ag@BONPs) as enhanced substrates, enabling it not only to cleanse pesticide residues from the surface to pulp of fruits and vegetables, but also to investigate the penetration dynamics of an array of pesticides (chlorpyrifos, thiabendazole, thiram, and acetamiprid). The findings challenge existing paradigms, unveiling a previously unnoticed weakening process during pesticide invasion and revealing the surprising permeability of non-systemic pesticides. Of particular note is easy to overlook that the combined application of pesticides can inadvertently intensify their invasive capacity due to pesticide interactions. The innovative study delves into the realm of pesticide penetration, propelling a paradigm shift in the understanding of food safety. Meanwhile, this strategy provides strong support for the cutting-edge application of SERS imaging technology and also brings valuable reference and enlightenment for researchers in related fields.

Systematic approaches to machine learning models for predicting pesticide toxicity

Pesticides play an important role in modern agriculture by protecting crops from pests and diseases. However, the negative consequences of pesticides, such as environmental contamination and adverse effects on human and ecological health, underscore the importance of accurate toxicity predictions. To address this issue, artificial intelligence models have emerged as valuable methods for predicting the toxicity of organic compounds. In this review article, we explore the application of machine learning (ML) for pesticide toxicity prediction. This review provides a detailed summary of recent developments, prediction models, and datasets used for pesticide toxicity prediction. In this analysis, we compared the results of several algorithms that predict the harmfulness of various classes of pesticides. Furthermore, this review article identified emerging trends and areas for future direction, showcasing the transformative potential of machine learning in promoting safer pesticide usage and sustainable agriculture.

In situ imaging of the spatial and temporal penetration of organic pollutants into microplastics via surface-enhanced Raman spectroscopy

Understanding the spatial and temporal penetration patterns of organic pollutants in microplastics (μP) is important for evaluating their environmental and biological impacts, such as the "Trojan Horse" effect. However, there is a lack of an effective method to monitor the penetration processes and patterns in situ. This study aimed to develop a simple and sensitive approach for in situ imaging of organic pollutant penetration into μP. The novel method was developed using surface-enhanced Raman spectroscopy (SERS) coupled with gold nanoparticles as nanoprobes that could sensitively detect organic pollutants in low-density polyethylene (LDPE) μP spatially and temporally. The detection limit of this SERS-based method was 0.36 and 0.02 ng/mm² for ferbam (pesticide) and methylene blue (synthetic dye), respectively. The results showed that both ferbam and methylene blue could penetrate LDPE μP. The penetration depth and amount increased as the interaction time increased. Most of the absorbed organic pollutants accumulated within the top 90 μm layer of the tested μP. Compared to methylene blue, ferbam was more quickly absorbed and achieved higher accumulation in μP with a maximum of 32.57 ng/mm² after 168 h interaction. This pioneering study clearly demonstrated that SERS mapping is a sensitive and in situ approach to visualize and quantify the penetration patterns of organic pollutants in μP. The new approach developed here can advance our understanding of μP as pollutant carriers and their influence on the environmental fate, behavior, and biological impacts of organic pollutants.

Understanding the impact of a non-ionic surfactant alkylphenol ethoxylate on surface-enhanced Raman spectroscopic analysis of pesticides on apple surfaces

Pesticide active ingredients (AIs) are often applied with adjuvants to facilitate the stability and functionality of AIs in agricultural practice. The objective of this study is to investigate the role of a common non-ionic surfactant, alkylphenol ethoxylate (APEO), on the surface-enhanced Raman spectroscopic (SERS) analysis of pesticides as well as its impact on pesticide persistence on apple surfaces, as a model fresh produce surface. The wetted areas of two AIs (thiabendazole and phosmet) mixed with APEO were determined respectively to correct the unit concentration applied on apple surfaces for a fair comparison. SERS with gold nanoparticle (AuNP) mirror substrates was applied to measure the signal intensity of AIs with and without APEO on apple surfaces after a short-term (45 min) and a long-term (5 days) exposure. The limit of detection (LOD) of thiabendazole and phosmet using this SERS-based method were 0.861 ppm and 2.883 ppm, respectively. The result showed that APEO decreased the SERS signal for non-systemic phosmet, while increased SERS intensity of systemic thiabendazole on apple surfaces after 45 min pesticide exposure. After 5 days, the SERS intensity of thiabendazole with APEO was higher than thiabendazole alone, and there was no significant difference between phosmet with and without APEO. Possible mechanisms were discussed. Furthermore, a 1% sodium bicarbonate (NaHCO₃) washing method was applied to test the impact of APEO on the persistence of the residues on apple surfaces after short-term and long-term exposures. The results indicated that APEO significantly enhanced the persistence of thiabendazole on plant surfaces after a 5-day exposure, while there was no significant impact on phosmet. The information obtained facilitates a better understanding of the impact of the non-ionic surfactant on SERS analysis of pesticide behavior on and in plants and helps further develop the SERS method for studying complex pesticide formulations in plant systems.

Novel Microneedle Patch-Based Surface-Enhanced Raman Spectroscopy Sensor for the Detection of Pesticide Residues

Pesticide residues are a global threat to human health, and conventional sensors fail to simultaneously detect pesticide residues on the surface and inside agricultural products. In this work, we present a new microneedle (MN) patch-based surface-enhanced Raman spectroscopy (SERS) sensor. The needles and the basement of MNs can simultaneously detect pesticide residues on the surface and inside agricultural products. The Ag nanoparticles and sodium hyaluronate/poly(vinyl alcohol) (HA/PVA) hydrogel used in this MN patch-based sensor efficiently amplify the Raman signals of the pesticide residues. In addition, the HA/PVA hydrogel can effectively and quickly collect the residues, allowing this sensor to detect pesticide residues more conveniently. Furthermore, the stepped structure of the MNs increases the sensor's surface area. Experimental results show that the sensor can detect thiram and thiabendazole (TBZ) pesticide residues with detection limits of 10^-7 and 10^-8 M, respectively. The detection process is minimally invasive and not harmful to agricultural products. The application of this MN patch-based SERS sensor can be extended to the safety and health monitoring of other plants and animals.

Real-time and in situ monitoring of organosilicon-induced thiram penetration into cabbage leaves by surface-enhanced Raman scattering mapping

BACKGROUND

Understanding pesticide penetration behavior is important for effective application of pesticides. However, there is a lack of an effective method to monitor pesticide penetration behavior and its changing process. In the present study, a novel surface-enhanced Raman scattering (SERS) mapping method was used for real-time and in situ tracking of the penetration behaviors of thiram and thiram-organosilicon mixture on cabbage leaves.

RESULTS

The results suggest that thiram has very weak ability to penetrate into cabbage leaves. However, when the thiram-organosilicon mixture was placed on leaf surfaces, a clear thiram signal was detected inside the leaf after 2 h of exposure, a strong signal was observed after 12 h, and the penetration depth of thiram was approximately 200 μm after 48 h.

CONCLUSION

SERS mapping was demonstrated to be a reliable method for in situ monitoring of organosilicon-induced thiram penetration into cabbage leaf over time. The present study provides a new reference for rationally selecting adjuvants, effectively applying pesticides, and reducing pesticides residue in food. © 2022 Society of Chemical Industry.

Sensitive and handy detection of pesticide residue on fruit surface based on single microsphere surface-enhanced Raman spectroscopy technique

HYPOTHESIS

Surface-enhanced Raman spectroscopy (SERS) has become an emerging and reliable tool for detecting pesticide residues due to its high sensitivity, fast testing speed and easy sample handling. SERS active substrates are the key to achieve efficient and sensitive detection. However, for the most widely used noble metal nanoparticles, there are problems of high noble metal nanoparticle usage and random aggregation. The micron-scale Raman spot is focused on multiple randomly aggregated nanoparticles during the test, resulting in poor reproducibility. Therefore, the development of micron-scale cost-effective SERS substrates with good reproducibility and simple detecting method is of great significance in practical detection.

EXPERIMENTS

Through deposition of silver nanoparticles (Ag-NPs) by chemical reduction on the surface of monodisperse sulfonated polystyrene (SPS) microspheres, micron-sized PS@Ag-NPs core-shell microspheres were prepared with excellent SERS activity. After that, two simple protocols (Method I and Method II) were explored for the determination of thiram on apple epidermis.

FINDINGS

Based on our developed strategy of the single microsphere SERS technique, we successfully fabricated uniform PS@Ag-NPs substrate with high SERS activity and excellent detection sensitivity. The single microsphere SERS technique possesses the capability of anti-dilutability and the utilization of ultra-low PS@Ag-NPs microsphere dosage, realizing qualitative and quantitative detection of thiram on apple with detection limits far below the standard stipulated by China and the European Union.

Raman Spectroscopy Can Distinguish Glyphosate-Susceptible and -Resistant Palmer Amaranth (Amaranthus palmeri)

The non-judicious use of herbicides has led to a widespread evolution of herbicide resistance in various weed species including Palmer amaranth, one of the most aggressive and troublesome weeds in the United States. Early detection of herbicide resistance in weed populations may help growers devise alternative management strategies before resistance spreads throughout the field. In this study, Raman spectroscopy was utilized as a rapid, non-destructive diagnostic tool to distinguish between three different glyphosate-resistant and four -susceptible Palmer amaranth populations. The glyphosate-resistant populations used in this study were 11-, 32-, and 36-fold more resistant compared to the susceptible standard. The 5-enolpyruvylshikimate-3-phosphate synthase (EPSPS) gene copy number for these resistant populations ranged from 86 to 116. We found that Raman spectroscopy could be used to differentiate herbicide-treated and non-treated susceptible populations based on changes in the intensity of vibrational bands at 1156, 1186, and 1525 cm-1 that originate from carotenoids. The partial least squares discriminant analysis (PLS-DA) model indicated that within 1 day of glyphosate treatment (D1), the average accuracy of detecting herbicide-treated and non-treated susceptible populations was 90 and 73.3%, respectively. We also found that glyphosate-resistant and -susceptible populations of Palmer amaranth can be easily detected with an accuracy of 84.7 and 71.9%, respectively, as early as D1. There were relative differences in the concentration of carotenoids in plants with different resistance levels, but these changes were not significant. The results of the study illustrate the utility of Raman spectra for evaluation of herbicide resistance and stress response in plants under field conditions.

What happens when pesticides are solubilised in binary ionic/zwitterionic-nonionic mixed micelles?

HYPOTHESIS

Surfactants have been widely used as adjuvants in agri-sprays to enhance the solubility of pesticides in foliar spray deposits and their mobility through leaf cuticles. Previously, we have characterised pesticide solubilisation in nonionic surfactant micelles, but what happens when pesticides become solubilised in anionic, cationic and zwitterionic and their mixtures with nonionic surfactants remain poorly characterised.

EXPERIMENTS

To facilitate characterisations by SANS and NMR, we used nonionic surfactant hexaethylene glycol monododecyl ether (C₁₂E₆), anionic sodium dodecylsulphate (SDS), cationic dodecyltrimethylammonium bromide (DTAB) and zwitterionic dodecylphosphocholine (C₁₂PC) as model adjuvant systems to solubilise 3 pesticides, Cyprodinil (CP), Azoxystrobin (AZ) and Difenoconazole (DF), representing different structural features. The investigation focused on the influence of solubilisates in driving changes to the micellar nanostructures in the absence or presence of electrolytes. NMR and NOESY were applied to investigate the solubility and location of each pesticide in the micelles. SANS was used to reveal subtle changes to the micellar structures due to pesticide solubilisation with and without electrolytes.

FINDINGS

Unlike nonionic surfactants, the ionic and zwitterionic surfactant micellar structures remain unchanged upon pesticide solubilisation. Electrolytes slightly elongate the ionic surfactant micelles but have no effect on nonionic and zwitterionic surfactants. Pesticide solubilisation could alter the structures of the binary mixtures of ionic/zwitterionic and ionic/nonionic micelles by causing elongation, shell shrinkage and dehydration, with the exact alteration being determined by the molar ratio in the mixture.

Compounded conservatism in European re-entry worker risk assessment of pesticides

We review the risk parameters and drivers in the current European Union (EU) worker risk assessment for pesticides, for example considering crop maintenance, crop inspection or harvesting activities, and show that the current approach is very conservative due to multiple worst-case default assumptions. As a case study, we compare generic exposure model estimates with measured worker re-entry exposure values which shows that external cumulative exposure is overpredicted by about 50-fold on average. For this exercise, data from 16 good laboratory practice (GLP)-compliant worker exposure studies in 6 crops were evaluated with a total number of 184 workers. As generic overprediction does not allow efficient risk management or realistic risk communication, we investigate how external exposure can be better predicted within the generic model, and outline options for possible improvements in the current methodology. We show that simply using averages achieves more meaningful exposure estimates, while still being conservative, with an average exposure overprediction of about 9-fold. Overall, EU risk assessment includes several numerically unaccounted "hidden safety factors", which means that workers are well protected; but simultaneously risk assessments are biased towards failing due to compounded conservatism. This should be considered for further global or regional guidance developments and performing more exposure-relevant risk assessment.

How does substrate hydrophobicity affect the morphological features of reconstituted wax films and their interactions with nonionic surfactant and pesticide?

HYPOTHESIS

Surfactants are widely used in agri-sprays to improve pesticide efficiency, but the mechanism underlying their interactions with the surface wax film on plants remains poorly understood. To facilitate physical characterisations, we have reconstituted wheat cuticular wax films onto an optically flat silicon substrate with and without octadecyltrimethoxysilane modification to control surface hydrophobicity.

EXPERIMENTS

Imaging techniques including scanning electron microscopy (SEM) unravelled morphological features of the reconstituted wax films similar to those on leaves, showing little impact from the different substrates used. Neutron reflection (NR) established that reconstituted wax films were comprised of an underlying wax film decorated with top surface wax protrusions, a common feature irrespective of substrate hydrophobicity and highly consistent with what was observed from natural wax films. NR measurements, with the help of isotopic H/D substitutions to modify the scattering contributions of the wax and solvent, revealed different wax regimes within the wax films, illustrating the impact of surface hydrophilicity on the nanostructures within the wax films.

FINDINGS

It was observed from both spectroscopic ellipsometry and NR measurements that wax films formed on the hydrophobic substrate were more robust and durable against attack by nonionic surfactant C₁₂E₆ solubilised with pesticide Cyprodinil (CP) than films coated on the bare hydrophilic silica. Thus, the former could be a more feasible model for studying the wax-surfactant-pesticide interactions.

Investigation of nonlinear relationship of surface enhanced Raman scattering signal for robust prediction of thiabendazole in apple

Thiabendazole (TBZ) is extensively used in agriculture to control molds; residue of TBZ may pose a threat to humans. Herein, surface-enhanced Raman spectroscopy (SERS) coupled variable selected regression methods have been proposed as simple and rapid TBZ quantification technique. The nonlinear correlation between the TBZ and SERS data was first diagnosed by augmented partial residual plots method and calculated by runs test. Au@Ag NPs with strong enhancement factor (EF = 4.07 × 10⁶) of Raman signal was used as SERS active material to collect spectra from TBZ. Subsequently, three nonlinear regression models were comparatively investigated and the competitive adaptive reweighted sampling-extreme learning machine (CARS-ELM) achieved a higher correlation coefficient (Rp² = 0.9406) and the lower root-mean-square-error of prediction (RMSEP = 0.5233 mg/L). Finally, recoveries of TBZ in apple samples were 83.02-93.54% with relative standard deviation (RSD) value < 10%. Therefore, SERS coupled CARS-ELM could be employed as a rapid and sensitive approach for TBZ detection in Fuji apples.

Preparation of a Chlorantraniliprole-Thiamethoxam Ultralow-Volume Spray and Application in the Control of Spodoptera frugiperda

Traditional pesticide spraying methods such as knapsack sprayers are inefficient. Ground application equipment is restricted by the terrain and damages the crops. Pesticides cannot be sprayed over a large area in a short time; thus, when there are concentrated outbreaks of pests with strong migration capacity, such as Spodoptera frugiperda, pests could not be controlled in a small area. Therefore, it is difficult to achieve a satisfactory control effect. Plant protection unmanned aerial vehicles (UAVs) have high efficiency and spray pesticides at low altitude and can suitably prevent and control the outbreak of pests. However, pesticide formulations suitable for UAVs are rare. In this study, we developed ultralow-volume (ULV) sprays suitable for plant protection UAVs. We studied their properties and found that the ULV sprays have good wettability and can be fully spread. The minimum contact angle on corn leaves is up to 19°, and the maximum retention is 2.7 times that of the reference product. They also have superior resistance to rain washout and can effectively extend the duration and utilization of pesticides. When sprayed by plant protection UAVs, the decrease rate of the ULV spray at 3 L/ha to S. frugiperda larvae is 81.31% and the control effect is 83.01%, both higher than those of the reference product 40% chlorantraniliprole-thiamethoxam water-dispersible granules (decrease rate 67.39%, control effect 70.35%), sprayed with a knapsack sprayer.

Improved analysis of propamocarb and cymoxanil for the investigation of residue behavior in two vegetables with different cultivation conditions

BACKGROUND

A modified quick, easy, cheap, effective, rugged and safe (QuEChERS) method was developed for the simultaneous determination of highly water-soluble propamocarb and hydrophobic cymoxanil in potato tuber and tomato fruit. Residue behaviors of the fungicides in open field or greenhouse were investigated for the safety evaluation of these two pesticides, and the effects of cultivation conditions, fungicide exposure and fruit size of tomato on residue level are discussed.

RESULTS

Vegetable samples were extracted with ammonia-acetonitrile, further purified with multiwall carbon nanotubes and analyzed using high-performance liquid chromatography tandem mass spectrometry. The method was validated with fortified samples at different concentration levels (0.05-2.0 mg kg^-1 ). Average recoveries ranged from 84 to 111% with relative standard deviations between 0.3 and 5.5%. Limits of quantification (LOQs) were set at the lowest spiking level of 0.05 mg kg^-1 . In tomato and cherry tomato, initial residue level of cymoxanil was below LOQ at recommended good agricultural practices. Propamocarb residues were affected by the cultivation conditions, with highest levels of 0.52 and 0.72 mg kg^-1 in open field and greenhouse, respectively. In addition, residues of propamocarb in cherry tomatoes were found to be present at 1.25 mg kg^-1 .

CONCLUSIONS

The field trial results showed that propamocarb and cymoxanil residues in potato tubers were below LOQ due to the tubers not being exposed to sprayed pesticides. The unexpected high residue levels in cherry tomato seem to indicate that cherry tomato with small size presents certain accumulative effects of propamocarb. © 2020 Society of Chemical Industry.

Rapid and Label-Free Immunosensing of Shiga Toxin Subtypes with Surface Plasmon Resonance Imaging

Shiga toxin-producing Escherichia coli (STEC) are responsible for gastrointestinal diseases reported in numerous outbreaks around the world as well as in the United States. Current detection methods have limitation to implement for rapid field-deployable detection with high volume of samples that are needed for regulatory purposes. Surface plasmon resonance imaging (SPRi) has proved to achieve rapid and label-free screening of multiple pathogens simultaneously, so it was evaluated in this work for the detection of Shiga toxins (Stx1a and Stx2a toxoids were used as the less toxic alternatives to Stx1 and Stx2, respectively). Multiple antibodies (Stx1pAb, Stx1-1mAb, Stx1-2mAb, Stx1d-3mAb, Stx1e-4mAb, Stx2pAb, Stx2-1mAb, Stx2-2mAb, and Stx2-10mAb) were spotted one by one by programed microarrayer, on the same high-throughput biochip with 50-nm gold film through multiple crosslinking and blocking steps to improve the orientation of antibodies on the biochip surface. Shiga toxins were detected based on the SPRi signal difference (ΔR) between immobilized testing antibodies and immunoglobulin G (IgG) control. Among the antibodies tested, Stx1pAb showed the highest sensitivity for Stx1 toxoid, with the limit of detection (LOD) of 50 ng/mL and detection time of 20 min. Both Stx2-1mAb and Stx2-2mAb exhibited high sensitivity for Stx2 toxoid. Furthermore, gold nanoparticles (GNPs) were used to amplify the SPRi signals of monoclonal antibodies in a sandwich platform. The LOD reached the level of picogram (pg)/mL with the help of GNP-antibody conjugate. This result proved that SPRi biochip with selected antibodies has the potential for rapid, high-throughput and multiplex detection of Shiga toxins.

Mapping of Pesticide Transmission on Biological Tissues by Surface Enhanced Raman Microscopy with a Gold Nanoparticle Mirror

We presented an improved surface-enhanced Raman scattering (SERS) mapping technique for the imaging of pesticides on biological samples including tomato leaves, fruits, and mouse skin using a gold nanoparticle mirror as the SERS substrate. The gold nanoparticle mirror was fabricated using 50 nm commercial citrate-capped gold nanoparticles upon the interface of water and a mediating solvent that was prepared using acetonitrile and hexane. The properties of the gold nanoparticle mirror were compared with gold nanoparticles, and the mirror displayed higher sensitivity with a limit of detection of 0.07 μg/cm² and better reproducibility with a relative standard deviation of 5.48% for the SERS mapping of pesticide (ferbam) on biological samples. The gold mirror-based SERS mapping technique was also used to investigate pesticide transmission from tomato fruit surfaces to mouse skin after 1 mg/cm² of pesticides was administered upon the fruit, and the results showed that about 23% of the pesticide was transmitted from the fruit to the mouse skin. We also found that pesticides on the contaminated hand could not be completely removed by routine rinsing with tap water for 2 min. This study provides an effective approach for the imaging of pesticides on biological tissues that would facilitate research on pesticide behaviors both on and in biological systems.

Combining Headspace Solid-Phase Microextraction and Surface-Enhanced Raman Spectroscopy To Detect the Pesticide Fonofos in Apple Juice

We developed an innovative approach that couples headspace solid-phase microextraction (SPME) with surface-enhanced Raman spectroscopy (SERS) to detect a volatile pesticide (i.e., fonofos) in a liquid complex matrix (i.e., apple juice). A gold nanoparticles-coated fiber was fabricated by reducing gold(III) on a chemically etched stainless steel wire to extract pesticide, using SPME. The fabricated fibers were then tested by a headspace-SPME method and a dip-SPME method, followed by SERS detection of fonofos in water and apple juice samples. Using the headspace-SPME method, we can detect as low as 5 ppb of fonofos in water and apple juice, compared with the dip-SPME method, which cannot detect lower than 10 ppb in water and 50 ppb in apple juice. This study demonstrated the potential capability of the headspace-SPME-SERS method for rapid (within 30 min) and sensitive detection of volatile and vaporizable compounds in complex matrices. The developed method could be a potential alternative approach to the gas chromatography method. Future work is needed to optimize the fiber by minimizing signal variation, and it should be tested in a variety of targeted compounds and matrices.

Effectiveness of Commercial and Homemade Washing Agents in Removing Pesticide Residues on and in Apples

Removal of pesticide residues from fresh produce is important to reduce pesticide exposure to humans. This study investigated the effectiveness of commercial and homemade washing agents in the removal of surface and internalized pesticide residues from apples. Surface-enhanced Raman scattering (SERS) mapping and liquid chromatography tandem mass spectrometry (LC-MS/MS) methods were used to determine the effectiveness of different washing agents in removing pesticide residues. Surface pesticide residues were most effectively removed by sodium bicarbonate (baking soda, NaHCO₃) solution when compared to either tap water or Clorox bleach. Using a 10 mg/mL NaHCO₃ washing solution, it took 12 and 15 min to completely remove thiabendazole or phosmet surface residues, respectively, following a 24 h exposure to these pesticides, which were applied at a concentration of 125 ng/cm². LC-MS/MS results showed, however, that 20% of applied thiabendazole and 4.4% of applied phosmet had penetrated into the apples following the 24 h exposure. Thiabendazole, a systemic pesticide, penetrated 4-fold deeper into the apple peel than did phosmet, a non-systemic pesticide, which led to more thiabendazole residues inside the apples, which could not be washed away using the NaHCO₃ washing solution. This study gives us the information that the standard postharvest washing method using Clorox bleach solution for 2 min is not an effective means to completely remove pesticide residues on the surface of apples. The NaHCO₃ method is more effective in removing surface pesticide residues on apples. In the presence of NaHCO₃, thiabendazole and phosmet can degrade, which assists the physical removal force of washing. However, the NaHCO₃ method was not completely effective in removing residues that have penetrated into the apple peel. The overall effectiveness of the method to remove all pesticide residues diminished as pesticides penetrated deeper into the fruit. In practical application, washing apples with NaHCO₃ solution can reduce pesticides mostly from the surface. Peeling is more effective to remove the penetrated pesticides; however, bioactive compounds in the peels will become lost too.

Detection of Pesticide Residues in Food Using Surface-Enhanced Raman Spectroscopy: A Review

Pesticides directly pollute the environment and contaminate foods ultimately being absorbed by the human body. Their residues contain highly toxic substances that have been found to cause serious problems to human health even at very low concentrations. The gold standard method, gas/liquid chromatography combined with mass spectroscopy, has been widely used for the detection of pesticide residues. However, these methods have some drawbacks such as complicated pretreatment and cleanup steps. Recent technological advancements of surface-enhanced Raman spectroscopy (SERS) have promoted the creation of alternative detection techniques. SERS is a useful detection tool with ultrasensitivity and simpler protocols. Present SERS-based pesticide residue detection often uses standard solutions of target analytes in conjunction with theoretical Raman spectra calculated by density functional theory (DFT) and actual Raman spectra detected by SERS. SERS is quite a promising technique for the direct detection of pesticides at trace levels in liquid samples or on the surface of solid samples following simple extraction to increase the concentration of analytes. In this review, we highlight recent studies on SERS-based pesticide detection, including SERS for pesticide standard solution detection and for pesticides in/on food samples. Moreover, in-depth analysis of pesticide chemical structures, structural alteration during food processing, interaction with SERS substrates, and selection of SERS-active substrates is involved.