Optimisation using the finite element method of a filter-based microfluidic SERS sensor for detection of multiple pesticides in strawberry

Food Addit Contam Part A Chem Anal Control Expo Risk Assess. 2021 Apr;38(4):646-658. doi: 10.1080/19440049.2021.1881624. Epub 2021 Mar 10.

Abstract

This study developed an in-field analytical technique for food samples by integrating filtration into a surface-enhanced Raman spectroscopy (SERS) microchip. This microchip embedded a filter membrane in the chip inlet to eliminate interfering particulates and enrich target analytes. The design and geometry of the channel were optimised by finite-elemental method (FEM) to tailor variations of flow velocity (within 0-24 μL/s) and facilitate efficient mixing of the filtrate with nanoparticles in two steps. Four pesticides (thiabendazole, thiram, endosulfan, and malathion) were successfully detected either individually or as a mixture in strawberries using this sensor. Strong Raman signals were obtained for the four studied pesticides and their major peaks were clearly observable even at a low concentration of 5 µg/kg. Limits of detection of four pesticides in strawberry extract were in the range of 44-88 μg/kg, showing good sensitivity of the sensor to the target analytes. High selectivity of the sensor was also proved by successful detection of each individual pesticide as a mixture in strawberry matrices. High recoveries (90-122%) were achieved for the four pesticides in the strawberry extract. This sensor is the first filter-based SERS microchip for identification and quantification of multiple target analytes in complex food samples.

Keywords: FEM; pesticides; Food microfluidics; SERS; filtration.

MeSH terms

  • Finite Element Analysis*
  • Food Analysis* / instrumentation
  • Food Contamination / analysis*
  • Fragaria / chemistry*
  • Lab-On-A-Chip Devices*
  • Pesticides / analysis*
  • Spectrum Analysis, Raman / instrumentation
  • Surface Properties

Substances

  • Pesticides