Detection Of Pesticide Residues Research Articles

A balsam pear-shaped CuO SERS substrate with highly chemical enhancement for pesticide residue detection.

Simple and traditional hydrothermal fabrication of a novel balsam pear-shaped CuO with high SERS enhancementis presented. XRD (X-ray diffraction), SEM (scanning electronic microscopy), TEM (transmission electron microscope), HRTEM (high-resolution transmission electron microscope), UV-Vis, and Raman are adopted to ensure that this balsam pear-shaped CuO with dense nanoparticle protuberance is successfully prepared. The LOD of this CuO SERS substrate is 4.79μgL-1 with R6G as molecular probe. By using DFT (density functional theory) calculation and FDTD (finite difference time domainmethod) simulation, both EM (electromagnetic enhancement) and CM (chemical enhancement) mechanisms are investigated, and the results show that these two-enhancement mechanisms can coexist in this balsam pear-shaped CuO. Finally, the prepared substrate has been applied for the determination oftrace levels of paraquat in solution, and results show that its LOD for paraquat is275μgL-1 (optimum Raman band: 1646cm-1 Raman shift), which is better than the government standard in China. Adexterous and facile way for fabrication of CuO SERS-active substrates with low cost and high performance, quite promising in detection of chemically hazardous substances and pesticide residueis provided. Graphical abstract.

A magnetic multi-walled carbon nanotube preparative method for analyzing asymmetric carbon, phosphorus and sulfur atoms of chiral pesticide residues in Chinese herbals by chiral liquid chromatography-quadrupole/linear ion trap mass spectrometry determination

An analytical method for the determination of asymmetric carbon, phosphorus and sulfur atoms in chiral pesticide residues by magnetic multi-walled carbon nanotube sample pretreatment combined with chiral ultra-performance liquid chromatography/quadrupole/linear ion trap mass spectrometry (UPLC-MS/Qtrap) was developed and applied to chiral pesticide residues analysis in Chinese herbals. Eleven different chiral pesticides were found, and 36.4% were positive in Chinese herbals. Three plants containing detectable pesticide residues were observed in Dendrobium nobile, Panax notoginseng flowers and honeysuckle, in the order of decreasing detected concentration. High detection frequencies of 26.1% for (R/S)-(±)-difenoconazole and 14.5% for (R/S)-(±)-metalaxyl and (R/S)-(±)-propiconazole were observed, the residual amount for (R/S)-(±)-difenoconazole, (R/S)-(±)-metalaxyl and (R/S)-(±)-propiconazole were 0.32 ~ 2.5 mg/kg, 0.022 ~ 0.23 mg/kg, 0.62 ~ 3.21 mg/kg respectively. The EF value of (R/S)-(±)-difenoconazole was 0.506 ± 0.046. The EF value of (R/S)-(±)-metalaxyl was lower than 0.5 in Dendrobium nobile, Panax notoginseng flowers, Panax notoginseng roots and hawthorn. The EF of (R/S)-(±)-propiconazole was not significantly enantioselective in honeysuckle and Panax notoginseng flowers. The enantioselectivity of various pesticide residues in different plants cannot be predicted from our existing knowledge and may closely depend on plant growth, environmental conditions or molecular structure.

Rapid nondestructive detection of mixed pesticides residues on fruit surface using SERS combined with self-modeling mixture analysis method

Mixed pesticides are usually applied to agricultural products to enhance agricultural production. However, their presence in the environment and food poses serious health risks to humans. Therefore, rapid and reliable detection methods for mixed pesticides residues are in need to minimize potential health hazards. Herein, a nondestructive and sensitive strategy was developed to determine thiram and thiabendazole (TBZ) mixture on fruit surface using surface-enhanced Raman spectroscopy (SERS) technology coupled with interfacial self-assembly gold nanorods (Au NRs) array substrates together with self-modelling mixture analysis (SMA) method. Firstly, a large area high-density Au NRs array was fabricated by organic-aqueous interfacial self-assembly to serve as a sensitive SERS substrate for simultaneously screening of thiram and TBZ on the fruit surface. Then, an SMA method was employed to identify and separate the Raman spectrum for each pesticide from the Raman spectra of the pesticides mixture on the contaminated fruit surface. Results showed that using SERS technique with the SMA method, qualitative and quantitative analyses of a single component from the spectra of the mixture were simultaneously realized, and the resolved pure spectrum of each pesticide was presented. The limits of detection (LOD) of pesticides on the surface of apple, tomato and pear were 0.041, 0.029 and 0.047 ng/cm2 for thiram, and 0.79, 0.76 and 0.80 ng/cm2 for TBZ, respectively. It was anticipated that the proposed SERS detection approach combined with SMA methods should pave the way for detecting multi-analytes in practical applications for agriculture and food safety inspection.

Detection of Pesticide Residues in Fruits and Vegetables: Degradation and Removal by Ozonolysis

We investigated effects of ozonization of the degradation and removal of pesticides residues in fruits and vegetables

Multiple Kinds of Pesticides Detection Based on Back-Propagation Neural Network Analysis of Fluorescence Spectra

Fluorescence spectroscopy attracted more and more attention in pesticide residue detection field because of its advantages of non-destructive, non-contact, high speed and no requirement of complex pre-process procedure. However, given that the concentration of the pesticide detected via fluorescence spectroscopy is calculated in accordance with the Beer-Lambert law, this method can only be used to detect samples containing a single kind of pesticide or several kinds of pesticides with completely different fluorescence which is not in accordance with practical cases. In this article, to overcome this disadvantage, back-propagation (BP) neural network algorithm was introduced to detect multiple kinds of pesticides via fluorescence spectroscopy. The results from four kinds of pesticides which are usually used for fruits and vegetables indicated the effectiveness of BP neural network algorithm.

Ultrasensitive fluorescent detection of pesticides in real sample by using green carbon dots.

Pesticides, widely used in modern agriculture, could potentially cause environmental pollution and affect human lives. Hence, the development of a highly sensitive sensing element to detect pesticide residues is crucial for food safety and ecosystem protection. Optical methods based on fluorescence properties provide an ideal approach for screening and quantification of these compounds in different medias including water, plant, and nutritional products. The development of fluorescence emitting carbon dot-based sensors for monitoring pesticides has attracted great attention in recent years. In comparison to other fluorophores, carbon dots have more promising optical features, higher quantum yields and better biocompatibility. This article aims to present a novel fluorescent sensing method of diazinon, glyphosate, and amicarbazone using plant-based carbon dots. A comprehensive characterization of carbon dots obtained from cauliflower was performed by methods including UV-visible, FTIR spectroscopy, fluorometry, AFM, DLS, and zeta sizer. Following this step, carbon dots were used to detect pesticides. The fluorescence quenching property of carbon dots has been utilized to identify detection limit of 0.25, 0.5, and 2 ng ml-1 for diazinon, amicarbazone, and glyphosate, respectively. Also, real sample study revealed that the detection of pesticides accompanied by our developed nano-sensor is repeatable and accurate. According to carbon dots specificity determination, the prepared nano sensor does not have the potential to identify “bromacil” and “dialen super” pesticides but the other three mentioned pesticides are detectable. The results confirm that synthesized green carbon dots are well qualified for application in food safety and environmental monitoring.

Sensitive fluorometric determination of quinclorac residues in rice

ABSTRACT Rice is one of the most important foods in the world due to its high nutritional value and production. Quinclorac, a selective herbicide, is one of the most detected pesticide residues in rice crops according to pesticide monitoring studies. Common methods for the determination of quinclorac in rice are very time-consuming and labour-intensive, so it is important to develop alternative sensitive and simple analytical methods able to detect quinclorac in food samples. Here we propose a fluorometric method for the screening of this herbicide at excitation/emission wavelengths of 238/358 nm/nm, respectively. A modified QuEChERS method was selected for sample treatment due to its simplicity and high recovery yields. The proposed method presents a detection limit of 2.5 ng mL−1 and satisfactory precision. Recovery experiments were performed in different kinds of rice (white and brown) at or below the Maximum Residue Limit established in European Union (5 mg kg−1), obtaining values close to 100%. All these characteristics ensure that the proposed method fulfils the requirements for its application in food control.

Highly Sensitive Detection of Pesticide Residues by LC-MS/MS Using Ammonia Solution as an Eluent

Highly Sensitive Detection of Pesticide Residues by LC-MS/MS Using Ammonia Solution as an Eluent

Magnetic assembled 3D SERS substrate for sensitive detection of pesticide residue in soil

Three-dimensional (3D) surface enhanced Raman scattering (SERS) substrates were produced by magnetic force assisting self-assembled nanoparticles in arrayed holes. Compared to ‘2D’ plasmonic structures used in conventional SERS substrates, the ‘hot spots’ existed on whole depth of the 3D SERS substrates, which greatly enhanced the sensitivity. The prepared 3D SERS substrate was able to detect 4-aminothiophenol with a concentration down to 1 pM. Furthermore, the substrate was applied to detect hexachlorobenzene residue in soil, indicating its great potential for rapid and sensitive detection of extreme low concentrated molecules, especially pollutants residues in foods and environments.

In Situ Recyclable Surface-Enhanced Raman Scattering-Based Detection of Multicomponent Pesticide Residues on Fruits and Vegetables by the Flower-like MoS2@Ag Hybrid Substrate.

Pesticides, extensively used in agriculture production, have received enormous attention because of their potential threats to the environment and human health. Hence, in this study, a kind of highly sensitive and stable hybrid surface-enhanced Raman scattering (SERS)-active substrates constructed with flower-like two-dimensional molybdenum sulfide and Ag (MoS2@Ag) has been developed, and then the above substrate was sequentially utilized in the recyclable detection of pesticide residues on several kinds of fruits and vegetables. In the first place, the excellent photocatalytic performance of the MoS2@Ag hybrid substrate was demonstrated, which was attributed to the inhibition of electron-hole combination after the formation of Schottky barrier between the Ag NPs and MoS2 matrix. Thereafter, two calibration curves with ultra-low limits of detection (LOD) as 6.4 × 10-7 and 9.8 × 10-7 mg/mL were established for the standard solutions of thiram (tetramethylthiuram disulfide, TMTD) and methyl parathion (MP), and then the recyclable assay of their single and mixed residues on eggplant, Chinese cabbage, grape, and strawberry was successfully realized. It is interesting to note that the detection recoveries from 95.5 to 63.1% for TMTD and 92.3 to 62.6% for MP are greatly dependent on the size and surface roughness of these foods. In a word, the MoS2@Ag composite matrix shows attractive SERS and photocatalysis performance, and it is expected to have the potential application on food safety monitoring.

Silver nanoparticle-assembled micro-bowl arrays for sensitive SERS detection of pesticide residue

It is of great significance to develop a simple and effective method for constructing large-scale high-quality surface-enhanced Raman scattering (SERS) substrate. Here, an Ag nanoparticle-assembled micro-bowl array was prepared by a close-packed polystyrene (PS) sphere monolayer templated electrodeposition approach. The fabricated Ag nanoparticle-assembled micro-bowl array shows high SERS sensitivity to rhodamine 6G (R6G) under an ultra-low concentration of 1 fM, and exhibits excellent SERS spectral uniformity with a small relative standard deviation (RSD) of 7.6% and good reproducibility (a RSD ∼8.2% for the average peak intensities from different batches of SERS substrates). The fabricated micro-bowl array SERS substrate was employed to detect pesticide residue (thiram and methyl parathion) on vegetables. The limit of detections (LODs) for the two pesticides are lower than the maximum residue limits (MRLs) set by the European Union respectively, showing promising application in rapid inspection of food safety.

Determination of thiram, propineb and metiram in mushroom by gas chromatography-mass spectrometry

To establish a method for determination of thiram, propineb and metiram in mushroom samples by gas chromatography-mass spectrometry(GC-MS). Insoluble heavy metal salts were converted into water-soluble sodium salts by alkaline buffer with strong chelating agents. Dithiocarbamates can be converted into different methyl ester compounds with ion pair methylation. The GC separation was performed on a DB-5 MS capillary column(30 m×0. 25 mm, 0. 25 μm). The pesticides were detected by GC-MS with selective ion monitoring(SIM) and quantified by external standard of working curve method. Methodsological verification was carried out based on optimized sample pretreatment and GC-MS condition. The concentrations of dithiocarbamates exhibited a good linear relationship with GC-MS within a certain range. The limits of detection of thiram, propineb and metiram were 0. 01, 0. 05 and 0. 05 mg/kg, respectively. Furthermore, the average recoveries were from 76. 98% to 93. 52%, and the maximum relative standard deviation was 11. 54%(n=6). This method is simple, sensitive, accurate and reliable. All the indices meet the requirements of pesticide residue detection.

Pesticide Analysis in Agricultural Products by GC-MS/MS Using STQ Method

As a method to detect pesticide residues in agricultural products, we evaluated the pretreatment of agricultural product samples by the solid-phase extracton technique with QuEChERS (STQ) method followed by GC-MS/MS with large-volume injection using a stomach-type glass-lined injector. This method satisfied the target criteria of recovery (70-120%) and the standard deviation of repeatability (RSD<25%) in 238-282 pesticides found in six types of agricultural products.

Multiple kinds of pesticide residue detection using fluorescence spectroscopy combined with partial least-squares models.

Compared with high-performance liquid chromatography and mass spectroscopy, fluorescence spectroscopy has attracted considerable attention in the field of pesticide residue detection due to its practical advantages of providing rapid, simultaneous analysis and non-destructive detection. However, given that the concentration of pesticide residue detected via fluorescence spectroscopy is calculated in accordance with the Beer-Lambert law, this method can only detect samples containing a single kind of pesticide or several kinds of pesticides with completely different fluorescences. Multiple partial least-squares (PLS) models are introduced in this work to overcome this disadvantage and achieve the concentration of zhongshengmycin, paclobutrazol, boscalid, and pyridaben, whose fluorescences are overlapping. The R squares of the models for zhongshengmycin, paclobutrazol, boscalid, and pyridaben were 0.9942, 0.9912, 0.9913, and 0.9847, respectively. Results indicated that fluorescence spectroscopy combined with multiple PLS models can be used to detect multiple kinds of pesticides in the water.

Pesticides and conservation of large ungulates: Health risk to European bison from plant protection products as a result of crop depredation

The coexistence of large mammals and humans in the contemporary landscape is a big challenge for conservationists. Wild ungulates that forage on arable fields are exposed to the negative effects of pesticides, and this problem also applies to protected species for which intoxication by pesticides may pose a health risk and directly affect the effectiveness of conservation efforts. In this paper we assessed the threat posed by pesticides to the European bison Bison bonasus, a species successfully restituted after being extinct in the wild. We studied samples of B. bonasus liver from three free-living populations in Poland (Białowieska, Knyszyńska, and Borecka forests) and captive individuals from breeding centres. LC-QTOF-MS/MS two-step analysis for the detection, identification and confirmation of pesticide residues in liver samples, which included MS and targeted MS/MS scans, was conducted. It was found that European bison are exposed to pesticides as a result of crop depredation: the presence of tetraconazole, fluopyram and diazinon residues in 12 liver samples was confirmed. The concentration levels of the detected substances were quite low, but in the liver samples more than one substance was usually found, and the potential health risk to European bison may result from the synergistic interaction of these substances. The place of occurrence of the population, abundance, and the management regime affect the exposure of European bison to pesticides. Due to the high conservation status of the European bison, the monitoring of intoxication by pesticides should be included in the conservation plans of this species. This issue should also be more widely included in the study of other wild ungulates because knowledge about the impact of pesticides on wildlife is still insufficient.

Rapid and sensitive detection of pesticide residues using dynamic surface‐enhanced Raman spectroscopy

AbstractPesticide residues are one of the major food safety concerns for consumers all over the world, and it is crucial to develop simple, rapid, and effective method for the detection of pesticide residues. In the study, we report the sensitive detection of pesticides with the dynamic surface‐enhanced Raman spectroscopy (dynamic SERS) method. The dynamic SERS method provides excellent detection sensitivity at the metastable state of plasmonic nanoparticles in the sessile drop, which is a critical state between the wet state and dry state during the volatilization process. With this simple and rapid method, the SERS performance towards four pesticides, paraquat, thiabendazole, tricyclazole, and isocarbophos, is investigated with silver nanoparticles (AgNPs) as the enhancing reagents. The characteristic SERS spectra of paraquat, thiabendazole, tricyclazole, and isocarbophos can be detected at concentrations down to 1 × 10−9 M, 5 × 10−9 M, 5.28 × 10−9 M, and 3.45 × 10−7 M, respectively. The pesticides are also discriminable at the same concentrations as the standard solution counterparts from the pesticides spiked vegetable extracts, and linear relationship can be drawn from the characteristic peak intensities and negative logarithm of concentrations of the four pesticides. Therefore, the simple and rapid dynamic SERS method shows great potential in the practical detection of pesticide residues.

Pesticide Residues and Health Risk Assessment in Tomatoes and Lettuces from Farms of Metropolitan Region Chile.

Over the last years, the detection of pesticide residues in the official food surveillance programs of Chile has been increased, mainly in fresh vegetables such as tomatoes and lettuces. The Metropolitana Region of Chile presents the highest detections in the country. The lack of evaluations of toxicological risks in human health have increased uncertainty of the potential effects of pesticides exposures in the Chilean population. This research aims to determinate health risks assessment of pesticide residues associated to tomatoes and lettuces produced in Metropolitana Region. The findings of this study reveal that tomatoes and lettuces cultivated in the MR show more than 50% of samples with one or multiple pesticides residues. From the total samples, 16% were over the Chilean Maximum Residue Levels (MRLs). The main pesticides detected in tomatoes and lettuces were methamidophos, methomyl, difenoconazole, cyprodinil and boscalid. The results obtained using the official data of the Ministry of Health of Chile (MINSAL) compared to the World Health Organization (WHO), describe relevant risks through the Estimated Daily Intakes (EDI), Hazard Quotients (HQ) and Hazard Index (HI) for the Chilean population due to high concentrations of methamidophos, methomyl and cyprodinil. More restrictions for the use of methamidophos, methomyl, difenoconazole, cyprodinil and boscalid and effective control programs should be implemented in order to mitigate the impacts on the Chilean population.

Selective extraction of fungicide carbendazim in fruits using β-cyclodextrin based molecularly imprinted polymers.

Considering the importance of developing a new analytical approach for pesticide residue detection for the sake of ensuring food safety, a β-cyclodextrin based molecularly imprinted polymer was prepared for selective determination of carbendazim. The polymers consist of a porous and hollow structure demonstrating the selective abundant adsorption sites for carbendazim molecule. The selectivity and adsorption capacity of the imprinted polymers were analyzed with dispersive solid-phase extraction and analyzed with high performance liquid chromatography coupled with ultraviolet. The results of imprinted polymers were higher than non-imprinted polymers with the maximum adsorption capacity of 3.65mg/g within 30 min of total adsorption time. The reusability of the imprinted polymers was determined to evaluate its effectiveness and stability, which proved that the polymers lost 10% efficiency within seven consecutive recycles. The developed method displayed good linearity over the concentration range of 0.05-2.0mg/L. The recovery percentage of 81.33-97.23 with relative standard deviations of 1.49-4.66% was obtained from spiked apple, banana, orange, and peach samples with a limit of detection of 0.03mg/L and a limit of quantification of 0.10mg/L (signal to noise ratio=3/10). The overall performance of the proposed method evident that this technique provided a desirable outcome and it can be used as a convenient approach, as it qualifies the analytical standards.

MOF@PEDOT Composite Films for Impedimetric Pesticide Sensors.

Due to its deleterious effects on health, development of new methods for detection and removal of pesticide residues in primary and derived agricultural products is a research topic of great importance. Among them, imazalil (IMZ) is a widely used post‐harvest fungicide with good performances in general, and is particularly applied to prevent green mold in citrus fruits. In this work, a composite film for the impedimetric sensing of IMZ built from metal‐organic framework nanocrystallites homogeneously distributed on a conductive poly(3,4‐ethylene dioxythiophene) (PEDOT) layer is presented. The as‐synthetized thin films are produced via spin‐coating over poly(ethylene terephtalate (PET) substrate following a straightforward, cost‐effective, single‐step procedure. By means of impedance spectroscopy, electric transport properties of the films are studied, and high sensitivity towards IMZ concentration in the range of 15 ppb to 1 ppm is demonstrated (featuring 1.6 and 4.2 ppb limit of detection, when using signal modulus and phase, respectively). The sensing platform hereby presented could be used for the construction of portable, miniaturized, and ultrasensitive devices, suitable for pesticide detection in food, wastewater effluents, or the assessment of drinking‐water quality.

Pesticide residues in tomato and tomato products marketed in Majmaah province, KSA, and their impact on human health

Over 22 samples of tomato, tomato paste, and ketchup collected from local markets, located in Majmaah Province, Saudi Arabia, were tested for the presence of 412 pesticide residues using the modified QuEChERS method, followed by LC-MS/MS and GC-MS/MS. About eight pesticide residues were detected in 36% of analyzed samples. The amount and frequency of detected pesticide residues were higher in tomato samples. All detected residues were below the maximum residue limits (MRLs). Multiple residues were detected in 27% of analyzed samples. Of the pesticides, cypermethrin was the most detected one followed by carbendazim. The average daily intake and health risk indices for Majmaah region population were estimated. The results showed that consumption of tomato and its products do not represent a risk to human health in this region. However, the presence of multiple residues in some samples necessitates regular monitoring of pesticide residues in tomato crop.