Pyraclostrobin is one of the most prevalent strobilurin fungicides from the broad-spectrum control of fungal diseases. The ever-increasing pesticides with the active ingredient of pyraclostrobin have been put into the agroecosystem in recent years. The survival of non-targeted organisms and the by-effects on human health can be induced by pyraclostrobin biomagnification within the food web. This study aims to elaborate on the fate characteristics and risk magnitude of pyraclostrobin after large-scale application that contributed to agroecosystem sustainability and dietary rationality. The registered crops included wheat, peanut, watermelon, and cucumber in the main production areas in China. The tracing of pyraclostrobin was performed on the multiple crop matrices using the self-developed ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). Some measurements were used to validate the specificity, linearity, matrix effect (ME), accuracy, precision, limit of detection (LOD), and limit of quantification (LOQ). LOD and LOQ were estimated to be 0.0001-0.0004, and 0.001 mg/kg for the wheat grains, wheat straw, peanut kernels, peanut straw, cucumber, and watermelon matrices, respectively. The average recoveries of the target analyte ranged from 81.2% to 112.2% for all fortification levels. The precision values were associated with the analytical methods. The relative standard deviations (RSD) were 0.7% to 18.1% for the pyraclostrobin in all matrices. The fate characteristics of pyraclostrobin were elucidated using the verified storage stability. Some parameters were selected to represent the occurrence, pharmacokinetics dissipation, and terminal magnitude of pyraclostrobin, including the original depositions, half-lives, and terminal magnitude. The concentrations of pyraclostrobin were attached the maximum of <0.001, ≤0.209, ≤0.048 mg/kg 2 h after the last application in peanut kernels, cucumber and watermelon, respectively, and 0.005-0.043 mg/kg 7 d after last application in the wheat grain. Significant differences were observed in the degradation dynamics of pyraclostrobin among different crops, with half-life of 1.9-4.7 d in watermelon, 2.6-7.5 d in cucumber, and 5.9-9.9 d in wheat grain. There was no half-life of peanut kernels without detecting the pyraclostrobin in any samples. The terminal level of pyraclostrobin in the wheat and peanut straws (0.187-75.291 mg/kg) was much higher than that in the edible part, including the wheat grain and peanut kernel (≤0.096 mg/kg). The long-term dietary risks of pyraclostrobin were further clarified for the population with the different regions, gender, and age using the supervised trials median residues (STMR) for the investigated crops that were recommended by the large-scale field trials. The risk quotients (RQ) were assessed as 123.959%-406.415% by the deterministic model, indicating out of the acceptable range. The risk quotients were inversely correlated to the age of the population. The children group was subjected to the greatest long-term risks of pyraclostrobin exposure from the dietary pathway. The population subgroup location in rural (RQ, 146.799%-406.415%) suffered more serious exposures than that in urban (123.959%-374.217%). A probabilistic model was further introduced for a more accurate estimation of dietary exposure. The total chronic risks (RQ) caused by consuming wheat grain and watermelon ranged from 0.025% to 11.309% from the 50 percentile to the 99.9 percentile, far less than 100%, indicating no potential risks for the population. The unacceptable chronic risk magnitude of pyraclostrobin was determined, according to the probabilistic distribution in the residual levels of the above four crops. Anyway, the hazard effects of pyraclostrobin from dietary pathways should be emphasized in daily life, especially for rural children group.

Pice quality is often required to monitor the routine pesticide residues. However, there are matrix sensitivity variations during operation. In this study, the UHPLC-MS/MS approach was developed to simultaneously determine the thiodicarb and methomyl in spices (chili, pepper, and spearmint). A systematic optimization of the chromatographic system was undertaken for the optimal separation, sensitivity, and robustness. Sample preparation was commenced with the acetonitrile extraction of the homogenized spice samples, followed by a clean-up step using a modified QuEChERS-based dispersive solid-phase extraction (d-SPE) procedure. Specifically, the materials were also employed as the 50 mg of primary secondary amine (PSA), 10 mg of graphitized carbon black (GCB), and 150 mg of anhydrous magnesium sulfate per 1.5mL of the extract. Three analytical columns with the stationary phases were evaluated after optimization under chromatographic conditions: A BEH C18 column (1.7 μm, 100 mm × 2.1 mm), a BEH HILIC column (1.7 μm, 100 mm × 2.1 mm), and an HSS T3 column (1.8 μm, 100 mm × 2.1 mm). The HSS T3 column was specifically designed to retain the polar compounds, indicating the markedly superior performance, thus providing for the excellent peak shape and sufficient retention for both analytes. Subsequent optimization was focused on the mobile phase composition. Four systems were compared: acetonitrile with 0.05% formic acid in water, methanol with 0.05% formic acid in water, pure acetonitrile with water, and pure methanol with water. The optimal methanol-water system was selected without the acid modification. There was a significant increase in the peak area, approximately 57% higher for the thiodicarb. The methomyl was improved to maintain the excellent peak symmetry, compared with the acidified systems. The flow rate was optimized in a range from 0.15 to 0.55 mL/min. A flow rate of 0.35 mL/min was identified as the ideal compromise, indicating a significant enhancement in the peak area, compared with the higher flow rates. The total time was also maintained. The column temperature was examined from 25°C to 65°C. A temperature of 55°C was found to maximize the detector response for both compounds. The thiodicarb shared a particularly significant 31.4% increase in the peak area, compared with 25°C. The injection volume was 2 μL, as the excessive volume compromised the chromatographic integrity. Mass spectrometric detection was performed using electrospray ionization in the positive mode (ESI+) with multiple reaction monitoring (MRM). The optimal performance was achieved by the effective separation of the thiodicarb and methomyl within 3 min, with the reproducible retention times of 2.68 and 2.10 min, respectively. The slope ratio of the matrix-matched versus solvent-based calibration curves revealed that there was extreme signal enhancement in the significant matrix, particularly for the methomyl in chili (ME = 1815.6%). Matrix-matched calibration was therefore essential for the accurate quantification. There was excellent linearity from 0.001 to 1 mg/L in all spice matrices, with the correlation coefficients (r) ≥ 0.9980. The accuracy and precision were validated after recovery tests at three fortification levels (0.002, 0.01, and 0.5 mg/kg) with five replicates. Mean recoveries ranged from 84.3% to 107.7%, with the CV of 3.0%-8.8%. The high sensitivity was obtained with an LOQ of 0.002 mg/kg and LOD of 0.16 × 10^-3 μg/kg, below the regulatory limits. The optimal, sensitive, and robust UHPLC-MS/MS can be expected to simultaneously quantify the thiodicarb and methomyl in the complex spice matrices. The systematic optimization of the chromatographic system, particularly the selection of the HSS T3 column and the methanol-water mobile phase, effectively mitigated the analytical challenges and detection sensitivity. Its suitability was also verified for the routine application in the regulatory monitoring and quality control laboratories, thereby strengthening the safety of the spices in the global food supply chain.

The risk assessment of dietary exposure to pesticide residues is a great concern in the fields of chemical risk management, food safety and human health. Effective quantitative risk assessment models are basic tools for assessing dietary exposure to pesticide residues. Based on a review of recent progress in the risk assessment of dietary exposure to pesticide residues, this paper summarizes the risk assessment models for dietary exposure to pesticide residues, including the deterministic assessment models, the probabilistic assessment models and the cumulative assessment models. The advantages and disadvantages of these models are compared in terms of their evolution, the situations to which they apply and the assessment demand, and the key factors such as model uncertainty, assessment software and database application are discussed. Based on the current status of the dietary risk assessment of pesticide residues in China, we highlight the urgency and importance of integrating model parameters, which will provide a scientific basis for improving the construction of risk assessment systems for dietary exposure to pesticide residues.