Pesticide Screening in Spinach Leaf Wash Water Using Microhematocrit Packed Capillary Tube Chromatography
Abstract The widespread and excessive application of pesticides on food crops presents a critical, long-standing threat to the global public health. Although advanced laboratory methods like gas chromatography (GC) and electrochemical assays offer high sensitivity, their reliance on expensive infrastructure and specialized reagents creates a dangerous bottleneck for decentralized, on-site food safety screening. To bridge this urgent diagnostic gap, this study introduces low-complexity, low-cost screening platforms utilizing capillary tube chromatography (CTC) to detect active pesticide ingredients in produce wash water. To simulate real-world conditions, commercial pesticide formulations were sprayed onto spinach leaves, and the surface residues were captured from the wash water via rapid liquid–liquid extraction. Following baseline validation of chlorpyrifos and cypermethrin using GC and thin-layer chromatography (TLC), the target compounds were successfully resolved inside packed CTC columns. By employing optimized KMnO4 or povidone-iodine visual staining protocols, pesticide contamination was identified by the naked eye without requiring laboratory instruments. This novel CTC platform overcomes the fragile structural constraints of traditional TLC plates, yet further experiments are required to determine its key performance parameters. Boasting an easily adjustable stationary phase, this method provides an accessible framework for immediate food safety monitoring, demanding further optimization for complex gradient capillary separations.
Authors
- An H. T. Phan
- Khoi Tan Nguyen (ORCID: https://orcid.org/0000-0003-3934-0371)
Institutions
- Iowa State University (US)
- Vietnam National University, Hanoi (VN)
Publication Details
- Journal
- Langmuir
- Published
- 2026-09-28
- DOI
- https://doi.org/10.1021/acs.langmuir.6c03908
- Primary Topic
- Analytical Chemistry and Chromatography
- Type
- article
- Field-Weighted Citation Impact
- 0.00