Improved analysis of 230 pesticide residues in three fermented soy products by using automated one-step accelerated solvent extraction coupled with GC-MS/MS.

Consumer concerns over healthy diets are increasing as a result of the toxicity and persistence of pesticide residues in foodstuffs. Developing sensitive and high-throughput monitoring techniques for these trace residues is seen as an essential step in ensuring food safety. An automatic and sensitive multi-residue analytical method was developed and validated for the simultaneous determination of 230 compounds, including pesticides and their hazardous metabolites, in fermented soy products. The method included preparing the sample using on-line extraction and clean-up system based on accelerated solvent extraction (ASE), then determining the analytes using GC-MS/MS techniques. The homogenized samples (soy sauce, douchi, and sufu) were automatically extracted at 80 °C and 10.3 MPa and at the same time, in situ cleaned by 300 mg of primary secondary amine (PSA) combined with 20 mg of hydroxylated multi-walled carbon nanotubes in an extraction cell. The method obtained excellent calibration linearity (r > 0.9220) and a satisfactory analysis of the targeted compounds, which were evaluated with matrix-matched calibration standards over the range of 5-500 µg L-1. The limit of detections (LODs) of analytes were in the range of 0.01-1.29 µg kg-1, 0.01-1.39 µg kg-1, and 0.01-1.34 µg kg-1 in soy sauce, douchi, and sufu, respectively. The limit of quantifications (LOQs), which defined as the lowest spiking level, were set at 5.0 µg kg-1. The recoveries were within 70-120 % for over 95 % of the analytes, and the relative standard deviations (RSDs) were below 13.6 %. Moreover, a positive detection rate of 47 % were obtained when the proposed method was used on 15 real fermented soy products. These results suggested that the developed high-throughput method is highly feasible for monitoring of these target analytes in trace level.

Development of a fully automated analytical platform based on static headspace-gas chromatography-tandem mass spectrometry for the analysis of five N-nitrosamines in dried aquatic products of animal origin.

BACKGROUND: The development of rapid and sensitive monitoring methods for trace N-nitrosamines (NAs) in foodstuffs is essential for mitigating the potential health risks to consumers. In the present study, an analytical platform based on one step fully automated static headspace sampling and gas chromatography-tandem mass spectrometry (GC-MS/MS) was developed and validated for the analysis of N-nitrosamines in dried aquatic products of animal origin. The samples and sodium chloride solution mixture were incubated in a heated headspace vial for analyte evaporation, coupled to automatic sampling and online GC-MS/MS analysis. The proposed method requires minimal sample preparation and organic solvent consumption. Five N-nitrosamines including N-nitroso dimethylamine, N-nitroso methyl ethylamine, N-nitroso pyrolidine, N-nitroso piperidine and N-nitroso diphenylamine were selected as model compounds to optimize the significant factors by a using Box-Behnken design. RESULTS: The optimum conditions achieved limits of detections in the range 0.08-0.29 µg kg-1 , with correlation coefficient over 0.998. Relative recoveries in dried aquatic product sample were in the range 76.9-92.4%, with relative SDs of 1.9-7.2%. CONCLUSION: These results confirm the reliability of the developed method for further application in trace level monitoring of the target analytes in foodstuffs. © 2022 Society of Chemical Industry.

Ethanol-ammonium sulfate system based modified quick, easy, cheap, effective, rugged, and safe method for the determination of four neonicotinoid pesticide and metabolite residues in two canned fruits.

As the pesticide and its metabolite residues in processed fruits could become a significant route of human exposure. The work presented herein focuses on developing a feasible quick, easy, cheap, effective, rugged, and safe method with improved extraction and cleanup system for the determination of imidacloprid, acetamiprid, thiamethoxam, and clothianidin (a metabolite of thiamethoxam) in canned fruits. The low toxic solvent ethanol was used to extract the analytes, and ammonium sulfate was used to promote phase separation. Moreover, the carboxylated multi-walled carbon nanotube acted as the clean-up sorbent for the removal of high solubility impurities. The proposed method was validated with fortified real samples at different concentration levels (20-200 µg/kg). Recoveries obtained from three spiked levels (20, 50, and 200 µg/kg) ranged from 74.9 to 86.4% with relative standard deviations of the intra-day and inter-day in the range of 0.8-5.5 and 2.0-7.1%, respectively. The limits of detection ranged from 0.2 to 0.5 and 0.2 to 0.6 µg/kg for orange and peach, respectively. The results demonstrated that the proposed method could be considered appropriate, and comparatively lower toxic for the analysis of neonicotinoid pesticide residues in canned fruit.

Recyclable nitrogen-containing chitin-derived carbon microsphere as sorbent for neonicotinoid residues adsorption and analysis.

Chitin-derived three-dimensional nanomaterials has tremendous potential in pesticide residue analysis as an attractive green substitute for toxic solvents. The work presented herein focuses on constructing the environmentally friendly nitrogen-containing chitin-derived carbon microspheres (N-CCMP) for the efficient adsorption of neonicotinoid pesticides (NPs) including acetamiprid, clothianidin, imidacloprid and thiamethoxam. The N-CCMP displayed hierarchical porous structure, uniform size distribution, and excellent specific surface area of 680.8 m2 g-1. The N-CCMP with N-heterocyclic ring structure and surface oxygen functional groups exhibited good affinity to NPs, which was beneficial for the rapid adsorption. Then, the N-CCMP were utilized as sorbent in extraction of NP residues. Under the optimum conditions, the relative recoveries in water and juice sample were in the range of 85 %-116 % and 74 %-108 %, with relative standard deviations (RSDs) of 0.1 %∼5.2 % and 0.7 %∼5.2 %, respectively. The extraction performance of N-CCMP were still over 80 % after 5 times of reuse.

Geographical origin traceability and identification of refined sugar using UPLC-QTof-MS analysis.

Authentication of geographical origin is essential to the food safety of refined sugar. This study aimed to determine the geographical origin traceability and authenticity of refined sugar in China. Ultra performance liquid chromatography-quadrupole time-of-flight Mass Spectrometry (UPLC-QTof-MS), instead of conventional stable isotope ratio mass spectrometer (IRMS), was used to detect the mass fragment ratios (Rδ-sucrose and Rδ-glucose) of refined sugar. These ratios could reflect the cultivation practice and environmental conditions. A total of 108 batches of samples were collected from six regions in China, and additional 72 samples were verified with support vector machines (SVM) model, in order to evaluate the accuracy of origin identification and composition prediction. Our results showed that 83.3% of the refined sugar was correctly classified based on the geographical region of origin under different environmental conditions. These findings indicate that the specified mass fragment ratio may be a promising approach for assessing the traceability and authenticity of refined sugar.