Microextraction technique associated with gas chromatography–mass spectrometry for determining pesticide residues in urine

Abstract

Urine is one of the biological matrices most used for detecting human contamination, as it is representative and easily obtained via noninvasive sampling. This study proposes a fast, accurate, and ecological method based on liquid–liquid microextraction with low-temperature partition (μLLE/LTP). It was validated to determine nine pesticides (lindane, alachlor, aldrin, chlorpyrifos, dieldrin, endrin, DDT, bifenthrin, and permethrin) in human urine, in association with gas chromatography coupled with mass spectrometry (GC–MS). The technique was optimized through a factorial design. The best conditions for the simultaneous extraction of the analytes comprised the addition of 600 µL of water and 600 µL of acetonitrile (extracting solvent) to a 500-µL urine sample, followed by vortexing for 60 s. By freezing the samples for 4 h, it was possible to extract the pesticides and perform the extract clean-up simultaneously. The parameters selectivity, linearity, limit of detection (LOD), limit of quantification (LOQ), precision, and accuracy were used to appraise the performance of the method. Good values of selectivity and linearity (R² > 0.990), LOQ (0.39–1.02 μg L⁻¹), accuracy (88–119% recovery), and precision (%CV ≤ 15%) were obtained. The μLLE/LTP–GC–MS method was applied to authentic urine samples collected from volunteers in Southeast Brazil.

Keywords:

• Pesticide residues
• biological sample
• sample preparation
• µLLE/LTP–GC–MS
• clean-up
• method validation

Disclosure statement

No potential conflict of interest was reported by the authors.

Data availability statement

The authors agree to make available data and materials supporting the results or analyzes presented in our article upon reasonable request.

These data refer to the results obtained during the optimization and validation of the method, which were presented in tables and figures, as well as the data obtained for the authentic samples.

Additional information

Funding

The authors would like to thank the Brazilian Agencies: Fundaçãode Amparo à Pesquisa do Estado de Minas Gerais (FAPEMIG), ConselhoNacional de Desenvolvimento Científico e Tecnológico (CNPq). Also, this study was financed in part by the Coordenação de Aperfeiçoamentode Pessoal de Nível Superior – Brasil (CAPES) – Finance Code 001.