Determination of multi-pesticide residues in vegetable products using a "reduced-scale" Quechers method and flow-modulated comprehensive two-dimensional gas chromatography-triple quadrupole mass spectrometry

Pesticide contamination pattern from Morocco, insights into the surveillance situation and health risk assessment: a review

The widespread application of pesticides in Morocco's agriculture renders their monitoring in food and environmental samples very necessary. Recent years have witnessed a growing interest in reporting studies related to the monitoring of pesticide residues in food, water, groundwater, and soil as well as their quantitative health risk assessment. Most published studies have been done by university researchers. However, the lack of research reproducibility remains a problem that considerably limits the possibility of exploiting data from the literature. Our study involves an extensive literature review utilizing search engines with keywords like "pesticide residues," "monitoring," "vegetables and fruits," "water and soil," "risk assessment," and "Morocco" from 2009 to 2023. Analysis of pesticide residues in foodstuffs and environmental samples highlights concerns over compliance with EU regulations, the health risks associated with pesticide exposure, and the necessity for comprehensive monitoring and risk assessment strategies. This paper could help influence policies to develop a strategy and action plan for the sound management of pesticides, including measures to reduce their use, raise awareness, and monitor compliance. Also, this paper could be useful for scientists interested in understanding the current situation and challenges regarding pesticide residues in Morocco, as well as countries with which commercial links exist.

Dual sorbent coating based magnet-integrated fabric phase sorptive extraction as a front-end to gas chromatography-mass spectrometry for multi-class pesticide determination in water samples

Magnet-integrated fabric phase sorptive extraction (MI-FPSE) is a sample preparation technique that has proved to be a powerful tool for environmental analysis. The fabrication and application of magnet-integrated dual sorbent-based FPSE membrane prepared by combining two different sol-gel sorbent-coated disks of different polarities together with a magnetic bar inserted between the two membranes to allow the stirring, was examined as novel preparation technique that not required samples pretreatments. The dual sorbent-based sample preparation platforms (made up of poly(tetrahydrofuran) and Carbowax 20M) were used for the extraction of seven classes of pesticides from ambient surface water samples prior to their determination by gas chromatography-mass spectrometry. Initially, different single and dual sol-gel sorbent-based MI-FPSE membranes were evaluated in terms of their extraction efficiency. The MI-FPSE with dual sol-gel sorbents were found to be superior to the single-materials MI-FPSE devices in terms of extraction recovery. The main parameters affecting the MI-FPSE extraction protocol (e.g., adsorption time, sample volume, stirring rate, salt addition, eluent type, desorption time and elution volume) were investigated. The selected extraction protocol enabled detection limits in the range between 0.001 and 0.16 ng mL-1. Furthermore, good relative standard deviation values for the intra-day and inter-day repeatability studies were obtained and were lower than 5.9 and 9.9 %, respectively. The proposed method was successfully used for the multi-class analysis of environmental surface water samples.

Evaluation of convolutional neural network for non-destructive detection of imidacloprid and acetamiprid residues in chili pepper (Capsicum frutescens L.) based on visible near-infrared spectroscopy

Consumption of agricultural products with pesticide residue is risky and can negatively affect health. This study proposed a nondestructive method of detecting pesticide residues in chili pepper based on the combination of visible and near-infrared (VIS/NIR) spectroscopy (400-2498 nm) and deep learning modeling. The obtained spectra of chili peppers with two types of pesticide residues (acetamiprid and imidacloprid) were analyzed using a one-dimensional convolutional neural network (1D-CNN). Compared with the commonly used partial least squares regression model, the 1D-CNN approach yielded higher prediction accuracy, with a root mean square error of calibration of 0.23 and 0.28 mg/kg and a root mean square error of prediction of 0.55 and 0.49 mg/kg for the acetamiprid and imidacloprid data sets, respectively. Overall, the results indicate that the combination of the 1D-CNN model and VIS/NIR spectroscopy is a promising nondestructive method of identifying pesticide residues in chili pepper.

Monitoring 432 potential pesticides in tomatoes produced and commercialized in Souss Massa region-Morocco, using LC-MS/MS and GC-MS/MS

In this work, we monitored 432 pesticide residues in 39 tomato samples (cherry tomato) obtained from local markets in Souss Massa region-Morocco. We used a QuEChERS combined with LC-MS/MS and GC-MS/MS, and the method was validated based on SANTE 11312/2021 guideline. The limits of quantification (LOQ) obtained for most of the pesticides analyzed are at the limit with default EU MRLs or well below other EU MRLs. Recoveries (between 70 and 120%) and RSDs (≤20%) are satisfactory for more than 95% of the analytes at spiking level of 0.01 mg/kg and more than 97% at 0.1 mg/kg. The results indicated that 22 out of 39 tomato samples are positives and the most of our samples had levels lower than the maximum residue levels (MRLs) with average concentrations between 0.011 and 0.156 mg/kg. The most found pesticides were azoxystrobin and difenoconazole in tomato (7 samples). Only buprofezin (0.095 mg/kg) was found above the EU MRLs (0.01 mg/kg). Also, banned pesticides namely benalaxyl, spirodiclofen and imidacloprid have been detected. The results of our study confirm the previous findings and gives insights on the occurrence of different pesticides in tomato samples from Souss Massa region-Morocco.

Direct extraction with acetonitrile of hemp seed oil for the analysis of pesticides by using comprehensive two-dimensional gas chromatography-triple quadrupole mass spectrometry

The method herein described involves a rapid and limited-volume (0.5 mL of acetonitrile) solvent-extraction sample preparation process, for pesticide determination in hemp seed oil. The extraction method was characterized by the absence of both clean-up or pre-concentration steps. The extracts were directly analyzed through cryogenic-modulation comprehensive two-dimensional gas chromatography coupled to triple quadrupole mass spectrometry. The novelty characterizing the present research [compared to a previous one (Arena et al., 2023)] is related to the extension of the number of pesticides (97), and to the investigation of a more challenging matrix, contained in a vegetable oil of increasing interest among consumers. Linearity, limits of detection and quantification, accuracy, precision, recovery, and matrix effect were measured. Particular emphasis was devoted to the matrix effect, with the co-extracted matrix amount defined. Three international regulations (Canada, California, Europe) were considered, and the obtained limits of quantification were found to be too high in five (Canada) and twelve (Europe) cases, for a total number of 15 pesticides. The analysis of ten commercial samples showed the presence of seven pesticide residues in four of them, at concentration levels ranging from 0.02 to 0.98 mg kg-1, with most over the regulation residue limits.

Comprehensive two-dimensional gas chromatography- A discussion on recent innovations

Although comprehensive 2-D GC is an established and often applied analytical method, the field is still highly dynamic thanks to a remarkable number of innovations. In this review, we discuss a number of recent developments in comprehensive 2-D GC technology. A variety of modulation methods are still being actively investigated and many exciting improvements are discussed in this review. We also review interesting developments in detection methods, retention modeling, and data analysis.

Potential of GC-Combustion-MS as a Powerful and Versatile Nitrogen-Selective Detector in Gas Chromatography

Here, we show the potential and applicability of the novel GC-combustion-MS approach as a nitrogen-selective GC detector. Operating requirements to achieve reproducible and compound-independent formation of volatile NO species as a selective N-signal during the combustion step are described. Specifically, high temperatures (≥1000 °C) and post-column O2 flows (0.4 mL min-1 of 0.3% O2 in He) turned out to be necessary when using a vertical oven without makeup flow (prototype #1). In contrast, the use of a horizontal oven with 1.7 mL min-1 He as an additional makeup flow (prototype #2) required milder conditions (850 °C and 0.2 mL min-1). A detection limit of 0.02 pg of N injected was achieved, which is by far the lowest ever reported for any GC detector. Equimolarity, linearity, and peak shape were also adequate. Validation of the approach was performed by the analysis of a certified reference material obtaining accurate (2% error) and precise (2% RSD) results. Robustness was tested with the analysis of two complex samples with different matrices (diesel and biomass pyrolysis oil) and N concentration levels. Total N determined after the integration of the whole chromatograms (524 ± 22 and 11,140 ± 330 μg N g-1, respectively) was in good agreement with the reference values (497 ± 10 and 11,000 ± 1200 μg N g-1, respectively). In contrast, GC-NCD results were lower for the diesel sample (394 ± 42 μg N g-1). Quantitative values for the individual and families of N species identified in the real samples by parallel GC-MS and additional GC × GC-MS analyses were also obtained using a single generic internal standard.

Ultra-High-Performance Liquid Chromatography Quadrupole Time-of-Flight Mass Spectrometry for Simultaneous Pesticide Analysis and Method Validation in Sweet Pepper

Pesticides effectively reduce the population of various pests that harm crops and increase productivity, but leave residues that adversely affect health and the environment. Here, a simultaneous multicomponent analysis method based on ultra-high-performance liquid chromatography quadrupole time-of-flight mass spectrometry (UHPLC-QTOF-MS) pretreated by the QuEChERS method was developed to control the maximum residual levels. Among the 140 pesticides with high frequency of detection in agricultural products in Gyeongnam region in Korea for 5 years, 12 pesticides with high detection frequency in sweet pepper were selected. The analytical method is validated, linearities are r² > 0.999, limit of detection (LOD) ranges from 1.4 to 3.2 µg/kg, and limit of quantification (LOQ) ranges from 4.1 to 9.7 µg/kg, and the recovery rate was 81.7-99.7%. In addition, it was confirmed that a meaningful value of these parameters can be achieved by determining the measurement uncertainty. The results proved that parameters such as recovery rate and relative standard deviation of the analysis method were within international standards. Using the developed method, better and safer sweet peppers will be provided to consumers, and effective pesticide residue management will be possible by expanding to other agricultural products.

Development and validation of a multi-class analysis of pesticides in corn products by comprehensive two-dimensional liquid chromatography-tandem mass spectrometry

Due to the growing trend of organic food, there is still concern over the use of chemicals and pesticides in agriculture. In recent years, several procedures have been validated for the control of pesticides in food. In the present research, a comprehensive two-dimensional liquid chromatography coupled with tandem mass spectrometry is proposed for the first time for a multi-class analysis of 112 pesticides in corn-based products. Notably, a "reduced" QuEChERS-based method as extraction and clean-up procedure prior to the analysis, was successfully employed. Limits of quantification values were lower than the ones fixed by the European legislation; intra-day and inter-day precision were lower than 12.9% and 15.1%, respectively (at the 500 μg/kg concentration levels). Over 70% of the analytes provided recoveries between 70% and 120% range (at 50, 500 and 1000 µg/kg concentration levels) with standard deviation values below 20%. In addition, matrix effect values were in the range between 13% to 161%. The method was applied to the analysis of real samples, and three pesticides were detected at trace levels in both samples. The findings of this work pave the way for the treatment of complex matrices such as corn products.

A method for the determination of 70 pesticides in extra virgin olive oil based on a limited-volume solvent extraction step prior to comprehensive two-dimensional gas chromatography-tandem mass spectrometry

The goal of the present research was to develop a method based on a miniaturized solvent extraction step (using only 500 μL of acetonitrile, with no further clean-up or concentration processes) prior to cryogenic-modulation comprehensive two-dimensional gas chromatography-tandem mass spectrometry for the determination of seventy pesticides in extra virgin olive oil, exploiting the enhanced specificity and sensitivity of this technique. Limits of quantification were always below European legislation residue limits, intra-day precision was between 0.3 and 4.9% (at the 50 and 100 μg kg^-1 concentration levels), inter-day precision was between 1.6 and 6.1% (at the 100 μg kg^-1 concentration level), recovery (at the 20, 50, and 100 μg kg^-1 concentration levels) was in the 14-120% range, accuracy at the initial stage of the work (within repeatability conditions) was between 79 and 110%, while accuracy after 3 months (within intermediate precision conditions) was between 91 and 121% (at the 50 and 100 μg kg^-1 concentration levels). Finally, the matrix effect was always positive, between 16 and 197%. The method was applied to the investigation of twenty samples, and eleven of these were found to be contaminated.

Novel Dual-Color Immunochromatographic Assay Based on Chrysanthemum-like Au@polydopamine and Colloidal Gold for Simultaneous Sensitive Detection of Paclobutrazol and Carbofuran in Fruits and Vegetables

To ensure food safety and prevent the toxic effects of paclobutrazol (PBZ) and carbofuran (CAR) on humans, a sensitive and rapid method for the detection of PBZ and CAR in fruits and vegetables is required. Herein, a highly sensitive PBZ monoclonal antibody (PBZ mAb) and CAR monoclonal antibody (CAR mAb) with half-inhibitory concentrations (IC₅₀) at 0.77 and 0.82 ng mL⁻¹ were prepared, respectively. We proposed a novel dual-color immunochromatographic assay (ICA) with two test lines (T₁ and T₂) and an independent control line (C) based on chrysanthemum-like Au@Polydopamine (AuNC@PDA) and colloidal gold (AuNPs) for the simultaneous and sensitive detection of PBZ and CAR with naked-eye detection limits of 10 and 5 μg kg⁻¹, respectively. The limits of detection (LOD) for PBZ and CAR were 0.117 and 0.087 μg kg⁻¹ in orange, 0.109 and 0.056 μg kg⁻¹ in grape, and 0.131 and 0.094 μg kg⁻¹ in cabbage mustard, respectively. The average recoveries of PBZ and CAR in orange, grape, and cabbage mustard were 97.86−102.83%, with coefficients of variation from 8.94 to 11.05. The detection results of this method for 30 samples (orange, grapes, and cabbage mustard) agreed well with those of liquid chromatography–tandem mass spectrometry. The novel dual-color ICA was sensitive, rapid, and accurate for the simultaneous detection of PBZ and CAR in real samples.

Advanced tuning of the ion management parameters in GC × GC-HRMS using a Fourier transform Orbitrap mass analyzer for pixel-based data handling and multivariate analysis

GC × GC investigations are well known to generate a substantial amount of information-rich and structurally complex data, requiring advanced data processing strategies like chemometrics. Many workflows are available for data handling and processing, such as the peak-table and pixel-based approaches. The goal of this work is to present a solution based on method development to solve the missing pixel problem that may be encountered in experiments performed with GC and GC × GC coupled to the Fourier transform orbital ion trap (FT-Orbitrap) mass analyzer. Data input is vital for pixel-based chemometric analyses, as some post-processing solutions may lead to significant loss of chemical information in the data set. Hence, a key requisite is that the chemical information is consistently indexed in the data arrays for proper pixel-based data handling and analysis. In this study, we carefully evaluated the ion management parameters to preserve the intrinsic structure and information of the data arrays of the GC × GC-FT-Orbitrap for future pixel-oriented chemometric analysis. The most acceptable conditions yielded acquisition rates up to 42.6 spectra per s, while a routine setting of 24.7 Hz was successfully employed in analyses of different petroleum fractions, producing both consistent tensor sizes and acceptable peak reconstructions. A data acquisition rate of 24.7 spectra per s and a mass resolving power of 15 000 allowed the resolution of a mass split of only 0.004 Da - which is an interesting configuration for challenging applications in petroleomics. Using such advanced settings, the missing pixel problem was reduced from up to 30% to much less than 0.04% of the data array dimension. Thus, the proposed configuration can be employed in studies that require pixel-oriented multivariate data analysis.

Untargeted profiling and differentiation of geographical variants of wine samples using headspace solid-phase microextraction flow-modulated comprehensive two-dimensional gas chromatography with the support of tile-based Fisher ratio analysis

The volatile fraction of food, also called the food volatilome, is increasingly used to develop new fingerprinting approaches. The characterization of the food volatilome is important to achieve desired flavor profiles in food production processes, or to differentiate different products, with winemaking being one popular area of interest. In the present research, headspace solid-phase microextraction (HS SPME) coupled to flow-modulated comprehensive two-dimensional gas chromatography with time-of-flight mass spectrometry (FM GC×GC-TOFMS) was used to characterize geographical-based differences in the volatilome of five white "Grillo" wines (of Sicilian origin), comprising the five sample classes. All wines were produced with the same vinification method in 2019. To minimize the influence of minor bottle-to-bottle differences, three bottles of the same wine were randomly selected, and three samples were collected per bottle, resulting in nine sample replicates per wine. Particular emphasis was devoted to the operational conditions of a novel low duty cycle flow modulator. A fast FM GC×GC-TOFMS method with a modulation period of 700 ms and a re-injection period of 80 ms was developed. Following, the instrumental software was exploited to identify class-distinguishing analytes in the dataset via tile-based Fisher ratio analysis (i.e., ChromaTOF Tile). A tile size of 10 modulations (7 s) on the first dimension and 45 spectra (300 ms) on the second dimension was used to encompass average peak widths and to account for minor retention time shifting. Off-line software was used to apply an ANOVA test. A p-value of 0.01 was applied in order to select the most important class-distinguishing analytes, which were input to principal component analysis (PCA). The PCA scores plot showed distinct clustering of the wines according to geographical origin, although the loadings revealed that only a few analytes were necessary to differentiate the wines. However, a comprehensive flavor profile assessment underscored the importance of all the information output by the ChromaTOF Tile software.