Surface-Enhanced Raman Spectroscopy for Pesticide Analysis
Summary
Surface-enhanced Raman spectroscopy (SERS) harnesses amplified vibrational signals from molecules adsorbed onto noble-metal nanostructures, enabling the detection of pesticide residues at trace levels. By exploiting localised surface plasmon resonance, SERS substrates composed of gold, silver or hybrid materials concentrate electromagnetic fields at “hot spots”, dramatically boosting Raman scattering. This label-free, non-destructive approach facilitates rapid screening in complex matrices—fruit skins, soil, water and crop tissues—often with minimal sample preparation. Recent advances in substrate engineering have produced flexible, low-cost platforms and three-dimensional architectures that improve sensitivity and reproducibility. The integration of SERS with portable Raman spectrometers and chemometric or machine-learning algorithms has further refined quantitative analysis, mitigating challenges from substrate heterogeneity and background interference. Such innovations promise transformative applications in food safety monitoring, environmental surveillance and regulatory compliance, offering on-site, real-time assessment of pesticide contamination across global agricultural systems.
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Surface-Enhanced Raman Spectroscopy for Pesticide Analysis publication trend
The graph below shows the total number of articles in surface-enhanced raman spectroscopy for pesticide analysis across all publications each year (not limited to Nature Index journals).
Technical terms
Surface-enhanced Raman spectroscopy (SERS): A spectroscopic technique that amplifies Raman scattering of molecules on plasmonic substrates, enabling ultra-sensitive detection.
Localised surface plasmon resonance (LSPR): Collective oscillation of conduction electrons in metal nanostructures that intensifies electromagnetic fields at the surface.
Substrate: The plasmonic material—typically gold or silver nanostructures—used to generate the enhancement effect in SERS.
Enhancement factor (EF): The ratio of Raman signal intensity obtained with a SERS substrate to that without enhancement.
Limit of detection (LOD): The lowest concentration of an analyte that can be reliably distinguished from background noise.
QuEChERS: A streamlined sample-preparation method (Quick, Easy, Cheap, Effective, Rugged, Safe) for extracting pesticide residues from complex food and environmental matrices.
References
- Surface‐Enhanced Raman Scattering Imaging Assisted by Machine Learning Analysis: Unveiling Pesticide Molecule Permeation in Crop Tissues. Advanced Science (2024).
- A review on nanomaterial-based SERS substrates for sustainable agriculture. The Science of The Total Environment (2024).
- Handheld SERS coupled with QuEChERs for the sensitive analysis of multiple pesticides in basmati rice. npj Science of Food (2022).
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