Application of Automated Mini–Solid-Phase Extraction Cleanup for the Analysis of Pesticides in Complex Spice Matrixes by GC-MS/MS

Abstract

Abstract Background: Pesticide residues are routinely tested in spices for trade compliance. This results in a huge sample load for food testing laboratories and demands automation in sample preparation. Although there exists a method for the analysis of pesticides in fruits using an automated sample cleanup by mini–solid-phase extraction (mini-SPE) technique, no study is available to date on spices. Objective: This study aims to develop an automated sample cleanup method using mini-SPE technique in a range of spices, including chili powder, turmeric, black pepper, cumin, coriander, and cardamom. Methods: This automated sample preparation workflow involved an X-Y-Z instrument autosampler, and a set of mini-SPE cartridges comprising cleanup sorbents. Spice samples were extracted by acetonitrile, and the extract was put into an autosampler vial for automated mini-SPE cleanup before analysis by GC tandem MS. For an efficient cleanup, three different sorbent compositions were compared along with various automated workflows. Results: For the relatively simple matrixes (e.g., coriander, cumin, and cardamom), the LOQ for the target pesticides was 10 ng/g with acceptable recovery, and precision. The method provided an LOQ of 10 ng/g for around 77% of the compounds in the relatively complex matrixes (e.g., turmeric, chili powder, and black pepper). The remainder of the compounds had satisfactory recoveries at 20 ng/g and higher levels. Conclusions: Given its time effectiveness and efficient analytical performance, this method can be adopted in commercial food testing laboratories for time-bound analysis of a large volume of samples. Highlights: The study describes effectiveness of the automated mini-SPE cleanup in multiresidue analysis of pesticides in a range of spice matrixes. The method facilitates high-throughput residue analysis in compliance with the regulatory requirements of sensitivity and method performance.