Detection Of Pesticide Residues Research Articles

Simultaneous detection of mixed pesticide residues based on portable Raman spectrometer and Au@Ag nanoparticles SERS substrate

Simultaneous detection of mixed pesticide residues based on portable Raman spectrometer and Au@Ag nanoparticles SERS substrate

Development of a method for analysis and risk assessment of residual pesticides in ginseng using liquid and gas chromatography-tandem mass spectrometry.

In this study, we developed a method for detecting 335 pesticides in ginseng using liquid chromatography quadrupole mass spectrometry (LC-MS/MS) and gas chromatography quadrupole mass spectrometry (GC-MS/MS). Additionally, the linearity, sensitivity, selectivity, accuracy, and precision of the method was validated. The limits of detection (LOD) and limits of quantification (LOQ) for the instrument used in these experiments was 0.1-5.8μg/kg and 0.3-17.5μg/kg, respectively. The average recovery was 71.6-113.4%. From 2016 to 2019, 467 ginseng samples were analyzed, of which 304 samples detected pesticide residues, but most of them were below the standard. It can be observed that the hazard quotient (HQ) of ginseng for detected pesticides wasless than1, thus implying that the risk was low. Hence, in this study, we developed a specific, reliable, and suitable method for a fast and simultaneous analysis of 335 pesticides in ginseng.

An improved DCGAN model: Data augmentation of hyperspectral image for identification pesticide residues of Hami melon

The increasing concern over pesticide residues on Hami melon is due to the unregulated use of pesticides, which poses a potential food safety hazard. Thus, it is urgent to propose a method for the rapid and nondestructive detection of pesticide residues on the Hami melon. This study used short-wave infrared hyperspectral imaging (SWIR-HSI) to identify pesticide residues on the Hami melon. The data augmentation method based on improved deep convolutional generative adversarial networks (DCGAN) was proposed to expand Hami melon's spectral data with different pesticide residues. To determine the optimal training epoch, the 1-nearest neighbor (1-NN) classifier was used to evaluate the quality of the generated spectra. The effectiveness of the improved DCGAN was verified by three commonly used classifiers, including the decision tree (DT), random forest (RF), and support vector machine (SVM). The results showed that the performance of all three classifiers was improved to varying degrees by the improved DCGAN. The DT, RF, and SVM accuracy was improved by 13.13%, 7.50%, and 11.25%, respectively. Moreover, the SVM model achieved the highest accuracy of 93.13%. These findings indicated that the combination of SWIR-HSI and the improved DCGAN-based data augmentation method has good promise for detecting pesticide residues on Hami melon.

Portable organophosphorus pesticide detection device based on controllable microfluidic and luminol composite nanofibers

Excessive organophosphorus pesticide residues in food are a serious threat to human health, it is very urgent to develop a portable, low-cost, and high precision pesticide residue detection device to achieve rapid detection of organophosphorus pesticide residues. In this study, a portable organophosphorus pesticide detection device equipped with microfluidic and luminol composite nanofibers was developed. The microfluidic chip was designed and optimized by a combine of mathematical model and multi-physics coupling simulation. The luminol particles were solidly loaded on polyacrylonitrile (PAN) electrospinning film through electrospinning method to achieve efficient utilization of microfluidic chips and luminol fluorescent reagents. The influence of the mass fraction of luminol particle on the microstructure of electrospinning film was analyzed, and the optimal mass fraction was determined by measuring the fluorescent stability and fluorescent intensity. The electrospinning film and the microfluidic chip was loaded to an independently developed portable organophosphorus pesticide detection device, whose detection limit can reach 0.035 mg/L and the average detection time can reach 30 s. The portable organophosphorus pesticide detection device shows high stability, high detection accuracy and efficiency, which can be widely adopted in the detection of organophosphorus pesticides.

Research progress of electrochemical sensors for pesticide residue detection

Pesticides have played an important role in agricultural production as an effective means of rapid and efficient control of pests and diseases. However, their unreasonable use can lead to excessive pesticide residues in the environment and agricultural products, posing a great threat to the ecological environment and human health. Therefore, it is necessary to establish a new technique for pesticide residue analysis that is efficient, sensitive and practical. Electrochemical sensors are widely used in the detection of pesticide residues due to their high sensitivity, stability, selectivity, simplicity, fast speed and low cost. This article reviews the application and research progress of immuno, enzyme, nano and molecularly imprinted electrochemical sensors in pesticide residue detection, and gives an outlook on the future application of electrochemical sensors in pesticide residues detection.

Dynamics of pesticides in surface water bodies by applying data mining to spatiotemporal big data. A case study for the Puglia Region

Surface water pollution by pesticides is a primary concern in many parts of the world. Therefore, an effective monitoring program is essential to assess the environmental state of aquatic ecosystems and evaluate mitigation strategies.In the Puglia Region (southern Italy), a complex seasonal monitoring program for detecting pesticide residues in water was initiated in 2018 and is still underway (over four years). The program was based on site-specific assessments and identified 170 Plant Protection Products (PPPs) to identify residues in the surface water bodies of Puglia.In this context, the present work aims to analyse pesticide data obtained from the regional monitoring of rivers over four years using a multidisciplinary approach, which includes statistical methods, data mining, and mapping tools to extract as much information as possible.To this end, data mining was applied to identify the prevalent mixtures of pesticide residues found at the monitoring stations and correlate these results with possible causative factors. The results showed that surface water bodies are subject to different pressures derived from the massive use of PPPs, and several seasonal and territorial-related factors were identified to be strictly correlated with pesticide concentration results. Nine main PPPs mixtures have been identified in the Puglia River. Glyphosate, AMPA, imidacloprid, and azoxystrobin represent the main residues detected in the surface aquatic environments regarding the amount and frequency revealed.The methodological approach proposed in the present work can represent a good “model study” to be used by researchers to interpret water quality trends and data variability from long-term monitoring studies. Moreover, our results can significantly support the decision-making process and implementation of environmental mitigation measures by optimising the results of complex monitoring programs.

A novel nanogold sol SERS/RRS dual-mode assay for trace imidacloprid with Ti3C2Tx@Ti-MOFs/peptide bifunctional nanoprobe

The development of rapid, simple, and highly sensitive analytical methods for detecting pesticide residues is crucial for safeguarding the environment and human health. In this study, MXeneTi3C2Tx nanosheets are used to load a titanium-based metal-organic framework (Ti-MOFs) and imidacloprid peptide (PTIMI), and a novel bifunctional nanoprobe (TN@Ti-MOFs/PT) is prepared by irradiation in a domestic microwave oven and stirring at room temperature. Powder X-ray diffraction, transmission electron microscope and Fourier transform infrared spectrometer are used to characterize the prepared nanomaterials. It is found that TN@Ti-MOFs/PT not only specifically recognizes imidacloprid (IMI), but also catalyzes the nanogold indicator reaction to generate gold nanoparticles (AuNP) in an 80 ℃ constant temperature water bath. The generated AuNP can be directly used as an optical probe for resonance Rayleigh scattering (RRS) at wavelength of 370 nm. In the presence of the Victoria blue 4 R molecule probe, it shows a robust surface enhanced Raman scattering (SERS) signal at wavelength number of 1617 cm−1. When the target molecule IMI is added, it can interact with the PTIMI specific base sequence, resulting in PT chain shedding from the TN@Ti-MOFs/PT nanoprobe surface, exposing abundant redox sites and accelerating the redox charge transfer, resulting in AuNP increase and SERS/RRS signal enhancement. As a result, a highly sensitive and specific PT-based dual-mode biosensing platform is developed for the detection of trace IMI, with a linear range of 0.01–0.25 ng/mL and a detection limit of 0.0011 and 0.0039 ng/mL by SERS and RRS assays, respectively. To demonstrate its practical application, the platform is used to detect IMI in vegetable samples, with relative deviations of 1.36–5.86% and recoveries of 95.0–107%. Additionally, the mechanism of nanocatalysis enhancement is also investigated.

Simultaneous detection of acetamiprid and carbendazim based on Raman-silent spectral window tags-mediated surface-enhanced Raman scattering aptasensor coupled with magnetic separation

Surface-enhanced Raman scattering (SERS) has been widely used for detecting pesticide residues. Nevertheless, the spectral interference of sample matrix still exists, and the simultaneous detection of multiple pesticides is challenging. In this work, specific simultaneous detection of acetamiprid (ACE) and carbendazim (CBZ) in complex sample matrix was achieved by using two Raman tag molecules (prussian blue, PB; 4-(mercaptomethyl) benzonitrile, MBN) whose peaks were in the Raman-silent spectral window. Two Raman nanoprobes were synthesized by adding MBN and PB into the Au and Ag core-shell gap and coupled with two complementary DNA (cDNA), respectively. Meanwhile, two aptamer-incubated Fe3O4/Au nanoparticles were used as capture molecules. Results showed that the Raman intensity at 2077 cm−1 and 2228 cm−1 had an inverse tendency with ACE and CBZ concentrations, respectively. Under the optimal conditions of aptamer, cDNA concentration, and reaction volume ratio, the SERS aptasensor showed a wide linear range of 0.01 ∼ 1 mg/kg with limit of detection of 9.43 μg/kg to ACE and 9.17 μg/kg to CBZ. The result of recovery experiment showed that there was no significant difference between SERS method and HPLC method (p > 0.05). It turned out that the SERS aptasensor had a good resistance to spectral interference of matrix and easy separation, which can specifically detect ACE and CBZ in complex matrix simultaneously. SERS combined with nano-sensor elements will be conducive to the on-site detection of various hazardous substances in food safety.

An ultrasensitive electrochemical aptasensor based on hydroxylated black phosphorus/thionine/poly-l-lysine nanocomposite for acetamiprid detection

A highly sensitive aptamer electrochemical sensor based on hydroxylated black phosphorus /thionine/poly-l-lysine (hBP/TH/PLL) nanocomposite and Au nanoparticles (Au NPs) was herein introduced for detection of Acetamiprid. The hBP/TH/PLL nanocomposite was prepared through the capping effect of thionine and adhesion property of poly-l-lysine (PLL). The nanocomposite can maintain excellent electrical conductivity of black phosphorus and effectively prevent oxidation of black phosphorus. The sensor was based on hBP/TH/PLL composite and AuNPs, and used highly specific aptamers as sensor probes. It has advantages such as low detection limit, high selectivity, great repeatability and stability. Under optimum conditions, the linear range of aptamer electrochemical sensor is 10 fM to 1 μM and detection limit is 9.407 fM. The aptamer electrochemical sensor has great selectivity and anti-interference, and has a potential application prospect in the field of rapid trace detection of pesticide residues.

Dialdehyde starch-enclosed silver nanoparticles substrate with controlled-release “hotspots” for ultrasensitive SERS detection of thiabendazole

Pesticide residues have long been a major concern for food safety. In this study, a dialdehyde starch-encapsulated silver nanoparticles composite with controlled-release “hotspots” was developed as a surface-enhanced Raman scattering (SERS) substrate. At room temperature, most of the Ag NPs were encapsulated in dialdehyde starch, which is beneficial for improving stability, and when heated to the gelatinization point, Ag NPs are completely released and abundant hot spots are formed. We demonstrated sensitive detection of thiabendazole (TBZ) in or on the surface of an apple by means of two ways, i.e., detecting the analyte in solution after pretreatment and in-situ detecting the analyte by using a flexible paper-based substrate. The results showed that the detection limits of TBZ by the two ways were 0.052 ppm and 0.051 ppm respectively, and the recoveries of TBZ range from 96.80 % to 105.46 %. Overall, this SERS substrate shows great potential for pesticide residue detection in food.

Levels and safety assessment of pesticide residues in selected vegetables and fruits sold in Ikorodu, Lagos, Nigeria

Pesticides are widely used to boost agricultural output, thus making food consumption a major route of human pesticide exposure. This study was aimed at determining the safety of pesticide residues in vegetables and fruits sold in Ikorodu Markets, Lagos, Nigeria. The vegetables analyzed were lettuce (Lactuca sativa), spinach (Spinacia oleracea), cabbage (Brassica oleracea), cucumber (Cucumis sativus), and onion (Allium cepa), while the fruits were orange (Citrus aurantium), mango (Mangifera indica), and guava (Psidium guajava). Samples of the vegetables and fruits were subjected to mass spectrometry (GC-MS) analysis, and the values obtained were compared with the minimum risk levels (MRLs) recommended by the World Health Organization (WHO). Thereafter, the estimated daily intake (EDI) and health risk index (HRI) of the detected pesticide residues were calculated and compared with the acceptable daily intake. The GC-MS analysis of the vegetables detected chlorepyrifos-ethyl beyond the MRLs in lettuce, spinach, and cucumber; metalaxyl exceeded the MRLs in cabbage; while cyhalothrin, emamectin, acetaprid, carbendazime, and cypermethrin were detected within the MRLs. The analyses of the fruits revealed non- tolerable levels of chlorepyrifos-ethyl in orange; imidacloprid exceeded the MRLs in mango; and carbon disulfide was above the MRLs in guava. The EDI and HRI of the pesticides were within acceptable limits, but the HRI of cyhalothrin in lettuce and carbon disulfide in mango were not. The results suggest that the vegetables and fruits may predispose consumers to health hazards, with spinach and mango posing the greatest risk. Farmers need to comply with safety guidelines on pesticide use.

Determination of pesticide residues in almonds by LC-MS/MS and GC-MS: A study of method validation and matrix effects

This study was performed to detect pesticide residues in almond. QuEChERS method was validated for determination of 270 pesticides by liquid chromatography-tandem mass spectrometry (LC–MS/MS) and gas chromatography-mass spectrometry (GC–MS). The method had a suitable linearity (R2 ≥ 0.99). Limit of detection (LOD) and limit of quantification (LOQ) were ranged from 0.28 to 3.00 µg kg−1 and 0.92 to 9.98 µg kg−1 respectively. Average recoveries varied from 70.03 % to 119.82 %. Repeatability and intra-laboratory reproducibility of the method, expressed as RSDs were between 1.65–19.15 % and 1.77–19.42 %, respectively. Expanded relative uncertainties ranged from 15.82 % to 46.58 %. Although minimal matrix effects were observed in the LC-MS/MS analysis, a strong matrix effects were detected in the GC–MS analysis. The validated method was used collected for the analysis of collected 90 samples from fifteen different provinces in Turkey. The data showed that all the studied samples did not contain pesticides above the LOD values.

Plasma-Excited Nebulizer Gas-Assisted Electrospray Ionization: Enhancing the Sensitivity of Pesticide in Mass Spectrometry.

Liquid chromatography-mass spectrometry (LC-MS) is widely used in the detection of pesticide residues. However, the detection sensitivity of low-polarity pesticides by commonly used electrospray ionization may be severely suppressed, which greatly affects the limit of detection and repeatability. Herein, a plasma-excited nebulizer gas-assisted electrospray ionization (PENG-ESI) device has been developed. By introducing the discharge plasma formed by Tesla coil into the electrospray nebulizer gas channel, the sensitivity of low-polarity pesticides was significantly increased while maintaining sensitivity to polar pesticides. Under the optimized conditions, the limit of detection for S-bioallethrin was achieved at the level of 100 pg/g with good linearity (R2 > 0.99) and precision (RSD ≤ 4.61%). The matrix effect of a series of spiked matrix samples is less than 13.1%. Finally, different pyrethroid pesticide residues were successfully analyzed without separation, highlighting that the technology has potential application prospects in food quality control, environmental monitoring, and other fields.

Pesticide residues in fresh and processed edible mushrooms from Czech markets

ABSTRACT The occurrence of pesticide residues, their metabolites and degradation products in 49 edible mushrooms (fresh, dried, canned and frozen) was investigated. Using QuEChERS extraction, followed by liquid and gas chromatography coupled with tandem mass spectrometry, the samples collected from Czech markets were tested for 427 analytes. A total of 21 pesticide residues, their metabolites and pesticide synergists were found in quantifiable concentrations. The most frequently detected pesticide residues included prochloraz and its metabolites, metrafenone and carbendazim. Two mushroom samples were found to be in violation of the maximum residue level. In addition, the fate of 13 pesticides during the processing of fresh mushrooms was investigated. The processing factors calculated from the data ranged from 6.0 to 12.3 for drying and from 0.3 to 1.3 for deep-freezing. The results showed that most of the pesticide residues tested were stable under the conditions of mushroom processing.

Optimization and validation of an oxidation and solid-phase extraction procedure for analysis of imidacloprid and its metabolites in cereals using ultra-performance liquid chromatography tandem mass spectrometry

A simple and reliable ultraperformance liquid chromatography tandem mass spectrometry (UPLC-MS/MS) method was proposed for analysis of the total residues of imidacloprid and its 6-chloropyridinyl metabolites in cereals. The method consisted of extraction with acidic acetonitrile, conversion of the analytes into 6-chloronicotinic acid by oxidation, cleanup with C18 cartridges, and UPLC-MS/MS detection. The validation results met the requirements of the guidelines for the detection of pesticide residues in EU and China, including the linearity (R2 = 0.998), matrix effect (−0.5∼-7.1%), accuracy (75.1–109.6%), precision (3.5–13.0%), metabolite conversion efficiency (81.6–102.3%), and sensitivity (limit of detection (LOD) of 0.0015 mg/kg and limit of quantification (LOQ) of 0.0050 mg/kg). The established method met the requirements of the residue definition and the maximum residue levels (MRLs) of imidacloprid in cereals, and was further applied to investigate the residues and dissipation of imidacloprid and its metabolites in wheat samples after field application.

Pesticide residues detected in Colossoma macropomum by the modified QuEChERS and GC-MS/MS methods

This study aimed to detect pesticides in the muscle tissue of farmed tambaqui (Colossoma macropomum), in relation to good management practices (GMP) and prophylaxis and biosecurity measures. There were 54 fish farms randomly selected from the 138 found in the Microregion of Zona da Mata, RO - Brazil, for visits and collection of epidemiological data. There were extracted 24 muscle fragments were extracted from dorsolateral portion of the tail of five specimens tambaqui per fish farming. The methods of detection and quantification of pesticide residues were modified QuEChERS and GC-MS/MS. Most fish farms are small businesses and their production areas are smaller than a rural module. These ventures are an income alternative for rural producers, this information is confirmed in percentage of 88.89% (48/54) of the rural properties visited have livestock and agriculture as their main productive activity. Water monitoring was carried out in 70.37% of fish farms. However, with frequency of two water analyzes per year. Preventive and prophylactic measures taken were performed in 30% (17/54). In addition, 7% (4/54) of fish farmers reported using sodium chloride and/or using formalin as a secondary preventive measure. It is also important to mention that there was a report of administration of potassium permanganate in a fish farm, 2% (1/54). There were 12.49% (3/54) positive for at least one pesticide. The chemical compounds found Azosxystrobin (<LOQ), Epoxiconazole (<LOQ) and Chlorpyrifos (<LOQ). The presence of Azosxystrobin, Epoxiconazol and Chlorpyrifos in tambaqui muscle tissue samples was detected above acceptable limits by the PNCRC.

On-site rapid detection of multiple pesticide residues in tea leaves by lateral flow immunoassay

The application of pesticides (mostly insecticides and fungicides) during the tea-planting process will undoubtedly increase the dietary risk associated with drinking tea. Thus, it is necessary to ascertain whether pesticide residues in tea products exceed the maximum residue limits. However, the complex matrices present in tea samples comprise a major challenge in the analytical detection of pesticide residues. In this study, nine types of lateral flow immunochromatographic strips (LFICSs) were developed to detect the pesticides of interest (fenpropathrin, chlorpyrifos, imidacloprid, thiamethoxam, acetamiprid, carbendazim, chlorothalonil, pyraclostrobin, and iprodione). To reduce the interference of tea substrates on the assay sensitivity, the pretreatment conditions for tea samples, including the extraction solvent, extraction time, and purification agent, were optimized for the simultaneous detection of these pesticides. The entire testing procedure (including pretreatment and detection) could be completed within 30 min. The detected results of authentic tea samples were confirmed by ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS), which suggest that the LFICS coupled with sample rapid pretreatment can be used for on-site rapid screening of the target pesticide in tea products prior to their market release.

Portable multichannel detection instrument based on time-resolved fluorescence immunochromatographic test strip for on-site detecting pesticide residues in vegetables

In this work, a portable multichannel detection instrument based on time-resolved fluorescence immunochromatographic test strip (TRFIS) was proposed for on-site detecting pesticide residues in vegetables. Its hardware consisted of a silicon photodiode and excitation light source array, a mainboard of the lower machine with STMicroelectronics 32 (STM32) and a linear stepping motor. While detecting, cardboard with 6-channel TRFIS was pulled into the cassette by the stepping motor. The peak area of the test (T) line and control (C) line of each TRFIS was sampled and calculated by software, then the concentration of the detected pesticide was obtained according to the ratio of the T to C value. This instrument could sample 6-channel TRFIS within 30 s simultaneously, and it exhibited excellent accuracy with a 2.5% average coefficient of variation for each channel (n = 12). In addition, the TRFIS was constructed by using europium oxide time-resolved fluorescent microspheres to label the monoclonal antibody against acetamiprid and form a fluorescent probe, which was fixed on the binding pad. The TRFIS was used for the detection of acetamiprid in celery cabbage, cauliflower and baby cabbage. This instrument was used to complete the qualitative and quantitative analysis of the TRFIS, so as to enhance the practical application of the detection method. This TRFIS possessed excellent linearity ranging from 0.25 mg kg−1 to 1.75 mg kg−1 for the detection of acetamiprid, and the limit of detection were 0.056–0.074 mg kg−1 in the different vegetable matrix. The platform combines the accuracy and portability of traditional test strips with the highly sensitive and efficient fluorescence intensity recognition function of detection equipment, which shows a great application prospect of multi-channel rapid detection of small molecule pollutants in the field.

Novel and portable test strip platform for rapid and sensitive on-site detection of procymidone pesticide.

A novel and portable detection platform for procymidone (PRM) was developed by combining simple sample pretreatment, lateral flow test strips based on multi-branched gold nanoparticle (LFTS-MBGNP), and a smartphone. Based on the large surface area of MBGNPs, rapid detection of PRM was realized by simple naked eye observation. By utilizing a smartphone as a portable signal analyzer, ultrasensitive quantitative detection of PRM in red wine was realized with the limits of detection (LOD) of 1.60ng/mL, which was 3000 times lower than the US limit (5ppm). Moreover, rapid detection of four kinds of fruits and vegetables was achieved within 10min, with LODs of 4.34ng/g, 6.93ng/g, 8.99ng/g, and 5.03ng/g, respectively, which could meet the PRM limit of the European Union (10ng/g). Integrating the optimized QuEChERS pretreatment method, the developed platform realized a simple and sensitive on-site detection of PRM pesticide in foods and red wine within 45min. This platform provides a useful tool and new idea for rapid screening and detection of pesticide residues in food.

Disposable tungsten sulfide framed polydopamine nanostructure modified sensor for non-enzymatic electrochemical detection of organophosphate pesticide

Pesticide residues pose a global threat to human health, and conventional sensors cannot simultaneously detect pesticide residues on the surface and inside agricultural products. Therefore, it opens up an opportunity to develop efficient techniques for the optimal detection of pesticides residues, enhancing agricultural productivity while simultaneously reducing associated health risks This work presents a polydopamine functionalized tungsten sulfide self-assembled nanostructure (WS2-PDA) electrocatalyst capable of detecting organophosphorus paraoxon ethyl (PXL) pesticide. The structural properties of the WS2-PDA nanostructure were analyzed for their morphology, crystallinity using various microscopy and spectroscopic techniques. The electrochemical experiments involving cyclic voltammetry (CV) and differential pulse voltammetry (DPV) were conducted to investigate the electrochemical behavior of the WS2-PDA modified screen-printed carbon electrode (SPCE) toward PXL. Intermolecular interactions of polydopamine, presenting catechol, imine and amine functional group on the WS2 ionic surface via coordination complex enhance the binding ability, leading to improved ionic conductivity, electrode activity, and a higher active surface area ensued fast electron transferability. According to the findings, the DPV cathodic peak current response of the modified electrode revealed sensitive detection of PXL, with a lower detection limit (LOD) of 0.0021 μM (S/N = 3). Following that, the electrode exhibited two linear concentration ranges from 0.01 μM to 443.09 μM, and 443.09 μM to 521.34 μM, with a sensitivity of 0.310 µA µM−1 cm2. Likewise, the proposed sensors exhibited excellent repeatability, reproducibility, and selectivity over common interferents. Subsequently, it demonstrated outstanding stability with a relative standard deviation (RSD) of < 2.24%. Finally, the WS2-PDA/SPCE sensor achieved good recovery results in the presence of water, soil, and food samples.