Arnab Goon 1,2 , Raviraj Shinde 1 , Bappa Ghosh 1 , Kaushik Banerjee 1 Show Affiliations »
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. © AOAC INTERNATIONAL 2020. All rights reserved. For permissions, please email: journals.permissions@oup.com.
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. © AOAC INTERNATIONAL 2020. All rights reserved. For permissions, please email: journals.permissions@oup.com.
Entities: Chemical
Species
Mesh： See more »
Substances： See more »
Year: 2020
PMID： 31451131 DOI： 10.5740/jaoacint.19-0202
Source DB: PubMed Journal: J AOAC Int ISSN： 1060-3271 Impact factor: 1.913