基于通过型固相萃取-超高效液相色谱-高分辨质谱同时测定杨梅中29种农药残留

A rapid and accurate analysis method based on PRiME HLB pass-through solid-phase extraction (SPE) and ultra-performance liquid chromatography-high resolution mass spectrometry (UPLC-HRMS) was developed for the determination of 29 pesticide residues in bayberry samples. The bayberry samples were first extracted using acetonitrile by vortexing; then, the extract solution was salted out and purified by PRiME HLB pass-through solid-phase extraction (SPE) cartridges. Chromatographic separation was subsequently carried out on a Waters ACQUITY UPLC HSS T(3) column (100 mm×2.1 mm, 1.8 μm) using 5 mmol/L ammonium acetate in water and acetonitrile as the elution solvent. The electrospray ion source in positive (ESI(+)) mode and full mass-data-dependent MS(2) (full mass-ddMS(2)) mode were used for quantification by the matrix-matched external standard method. The LC conditions were first optimized, and two analytical columns, Waters ACQUITY UPLC HSS T(3) and Waters ACQUITY UPLC BEH C(18), were investigated for the 29 pesticides. The results indicated that the Waters ACQUITY UPLC HSS T(3) column showed better chromatographic retention. Moreover, composites of the mobile phase were also studied. Compared to the acetonitrile-formic acid aqueous solution system and acetonitrile-formic acid-ammonium acetate aqueous solution system, the acetonitrile-ammonium acetate aqueous solution system used as the mobile phase exhibited much better chromatographic behavior for most of the 29 pesticides. In particular, the MS responses of some of the target pesticides were significantly improved when using the ammonium acetate-acetonitrile system as the mobile phase. In addition, the sample pretreatment conditions for the 29 pesticides in bayberry samples were systematically optimized. The matrix effect (ME) for three different types of purification methods were applied to evaluate the purification efficiency for the 29 pesticides in the bayberry samples. The following results were obtained from the post-spiking experiments: (1) For graphitized carbon (GCB) SPE, the post-spiking recoveries of 29 pesticides in the bayberry samples were generally low, less than 60%. (2) For the QuEChERS method, the recoveries of most target pesticides improved. The pesticide ratio with recoveries ranging from 70% to 120% was found to be 41%; however, the pesticide ratio with recoveries of less than 60% was still high (35%). (3) For the PRiME HLB-based pretreatment method, the recoveries of the 29 pesticides obviously improved. The pesticide ratio with recoveries between 70% and 120% was up to 76%, while the pesticide ratios were only 14% and 10% for post-spiking recoveries of 60%-70% and >120%, respectively. Meanwhile, the recoveries of all 29 pesticides were found to be more than 60%. Therefore, the PRiME HLB-based method was better than the GCB SPE and QuEChERS methods for pretreatment of the 29 pesticides in the bayberry samples. In addition, the PRiME HLB-based pretreatment process does not require tedious operation processes such as activation, balance, and elution, and thus, the sample pretreatment time is greatly shortened. Under the optimal conditions, the 29 target pesticides showed good linearity in the range of 1.0-200.0 μg/L, with correlation coefficients (R(2)) higher than 0.999. The limits of detection (LODs) were 2.0 μg/kg for the 29 target pesticides. The recoveries of the pesticides spiked in the bayberry samples were in the range of 69.2%-135.6% at 6, 200, and 400 μg/kg, respectively, while the relative standard deviations (RSDs) in the range of 0.7%-14.6%. The proposed method based on PRiME HLB-pass through SPE-UPLC-HRMS was adopted to determine these 29 pesticides in 30 bayberry samples purchased from local and online markets. According to the results, pesticides such as methamidamine, difenoconazole, and tebuconazole were frequently detected in the bayberry samples. However, the maximum residue limits (MRLs) of methamidamine, difenoconazole, and tebuconazole in bayberry samples were not provided in GB 2763-2019. In summary, the developed method is fast, simple, sensitive, and accurate, and it can be applied for daily monitoring of pesticides in bayberry samples.