Plasmonic microsphere lens arrays-integrated microfluidic SERS chip for mixed pesticides identification with machine learning

Zhenyong Dong ¹, Feixiang Zheng ¹, Hao Wang ¹

⁰College of Engineering and Applied Sciences, Nanjing University, Nanjing 210093, PR China; Key Laboratory of Intelligent Optical Sensing and Integration of the Ministry of Education, Nanjing University, Nanjing 210009, PR China.

Journal of Hazardous Materials +

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January 1, 2026

View abstract on PubMed

Summary

This study presents a novel Surface-Enhanced Raman Scattering (SERS) microfluidic chip for rapid, on-site detection of mixed pesticides in food. The integrated system offers high sensitivity and accuracy for complex sample analysis, improving food safety testing.

Area Of Science

Analytical Chemistry
Spectroscopy
Materials Science

Background

Mixed pesticide residues complicate food safety analysis.
Surface-Enhanced Raman Scattering (SERS) offers sensitive pesticide detection but faces limitations.
Existing methods lack integrated automation for sample preparation, detection, and analysis.

Purpose Of The Study

To develop an automated SERS microfluidic system for rapid, on-site detection of mixed pesticides.
To overcome limitations of traditional SERS techniques in complex sample matrices.
To enhance sensitivity, stability, and analytical capabilities for food safety applications.

Main Methods

Developed a SERS microfluidic chip with plasmonic microsphere lens arrays for uniform SERS detection.
Integrated a micro-QuEChERS module for efficient pesticide extraction from complex matrices.
Employed a random forest-dual annealing algorithm for analyzing mixed pesticide spectra.

Main Results

Achieved low limits of detection (LOD) for 2,4-dichlorophenoxyacetic acid (1.15 nM), acetamiprid (0.63 nM), and thiabendazole (0.69 nM).
Demonstrated excellent linearity (R² > 0.998) and high average recoveries (90.8%-108.4%).
Quantified mixed pesticides with low mean absolute percentage errors (4.96%-7.72%) and rapid analysis time (15 minutes).

Conclusions

The developed SERS microfluidic system provides a rapid, sensitive, and automated solution for detecting mixed pesticides.
The integrated approach overcomes key challenges in SERS application for food safety.
This technology enables efficient on-site analysis of complex agricultural samples.

Keywords:

Mixed pesticides Plasmonic microsphere lens arrays SERS microfluidic chip Spectral parsing algorithm Surface enhanced Raman spectroscopy