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

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.

Graphical Abstract

KEYWORDS:

• Food microfluidics
• SERS; filtration
• FEM; pesticides

Disclosure statement

The authors declare that they have no conflict of interest.

Correction Statement

This article has been republished with minor changes. These changes do not impact the academic content of the article.

Additional information

Funding

This research was financially supported by the Robert T. Marshall Scholarship, USDA National Institute of Food and Agriculture (2018-67017-27880) and USDA NIFA Multi-state Project NC-1194.