A novel GC-MS/MS method for rapid, purification-free detection of 59 pesticide residues in rice, offering efficiency and accuracy in analysis.

Objective To establish a simple and rapid purification-free gas chromatography-tandem mass spectrometry (GC-MS/MS) method for the determination of 59 pesticide residues in rice including organophosphorus, organochlorine, carbamate, and pyrethroid. Methods: The sample was crushed and sieved, extracted with 5 mL n-hexane by shaking, centrifuged at low temperature, and the supernatant was taken and directly injected and detected by GC-MS/MS. Results: The 59 pesticides in this method showed a good linear relationship in the range of 2.00¦Ìg/kg~100¦Ìg/kg, the correlation coefficient was r>0.995; the detection limit (LOD) was 0.001¦Ìg/kg~3.5¦Ìg/kg, and the lower limit of quantification (LOQ) was 0.004 ¦Ìg/kg~12¦Ìg/kg, relative standard deviation 0%~17.7% (n=6), recovery rate 80.0%-108%. Conclusion This method is simple, fast, sensitive and accurate, and is suitable for the detection of 59 pesticide residues in rice.

In the contemporary agricultural landscape, ensuring the safety and quality of staple foods such as rice is paramount. This necessity has led to the development of sophisticated analytical techniques to detect and quantify pesticide residues. Among these techniques, gas chromatography-tandem mass spectrometry (GC-MS/MS) stands out for its sensitivity, accuracy, and efficiency. This article presents a novel GC-MS/MS method designed for the rapid, purification-free determination of 59 pesticide residues in rice, encompassing organophosphorus, organochlorine, carbamate, and pyrethroid compounds.

Objective

The primary objective of this study was to establish a straightforward and expedient GC-MS/MS methodology capable of accurately determining a wide range of pesticide residues in rice. By eliminating the need for purification steps, the method aims to reduce analysis time and complexity, making it more accessible for routine screening purposes.

Methods

The methodological approach adopted for this study involves several key steps. Initially, rice samples are prepared by crushing and sieving to ensure uniformity. Subsequently, a 5 mL aliquot of n-hexane is used to extract the pesticide residues from the prepared sample through a process of shaking. This mixture is then centrifuged at low temperatures to separate the phases, and the supernatant containing the extracted pesticides is directly injected into the GC-MS/MS system for analysis.

The analytical conditions were optimized to achieve the best sensitivity and specificity for the detection of the 59 pesticides of interest. The GC-MS/MS system parameters were carefully calibrated to facilitate the accurate identification and quantification of the target compounds.

Results

The results of this study are highly promising. The analytical method demonstrated excellent linearity for all 59 pesticides over the concentration range of 2.00 µg/kg to 100 µg/kg, with correlation coefficients (r) exceeding 0.995. The detection limits (LOD) of the method ranged from 0.001 µg/kg to 3.5 µg/kg, and the lower limits of quantification (LOQ) varied between 0.004 µg/kg and 12 µg/kg. Furthermore, the method exhibited commendable precision, with relative standard deviations (RSDs) ranging from 0% to 17.7% for six replicate analyses. The recovery rates for the pesticides were between 80.0% and 108%, indicating a high level of accuracy.

Conclusion

The study successfully introduces a simple, rapid, and efficient GC-MS/MS method for the detection of 59 pesticide residues in rice without the need for sample purification. The method’s sensitivity, accuracy, and broad coverage make it an ideal tool for the routine monitoring of pesticide residues in rice. It represents a significant advancement in the field of food safety analysis, offering a practical solution for ensuring the safety and quality of rice, a staple food consumed worldwide. This method’s development aligns with the growing need for more efficient and accessible techniques for pesticide residue analysis, contributing to the protection of public health and the environment.

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Original research was done by Zheng Xiyin, Chen Luying, Li Qiang, Quan Taipeng

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