Proficiency Testing of High-throughput Non-targeted Detection of Pesticide Residues in Edible Agricultural Products

In order to understand the technical level of high-throughput non-targeted detection of pesticide residues in China's inspection and testing institutions and improve the ability of food safety risk monitoring. Blank and added samples were prepared with organic apples as raw materials. F test and S_S≤0.3σ criterion were used to evaluate the uniformity of the samples. T test and |\overline\rmx-\overline\rmy |≤0.3σ criterion were used to evaluate the stability of the samples. In view of the fact that the existing evaluation technology did not consider the problem of high-throughput non-targeted detection, a new evaluation method was proposed. By establishing a two-dimensional (XY) classification, the number of pesticide detection (dimension X: qualitative) and the number of acceptable z-scores (dimension Y: quantitative) were evaluated. The c value was introduced as the primary evaluation index through qualitative satisfaction rate and quantitative satisfaction rate, while the false positive rate and false negative rate were used as the secondary evaluation index to comprehensively evaluate the detection ability of the laboratory. The results showed that a total of 20 laboratories participated in this proficiency testing, with a qualitative satisfaction rate of 70%, a quantitative satisfaction rate of 45%, and a comprehensive satisfaction rate of 40%. For laboratories with a c value of 0, further evaluation by secondary indicators showed that 87.5% of the laboratories did not show false positives and false negatives. In this study, qualitative analysis and quantitative analysis were combined to evaluate the results of high-throughput non-targeted detection of pesticide residues, which provided new ideas for the optimization of other ability evaluation methods.