Pesticides play a crucial role in the modern agricultural system, but growing concerns regarding their toxicity and environmental persistence necessitate the development of innovative detection methodologies to better monitor their impact. Surface-Enhanced Raman Scattering (SERS) has emerged as a promising new tool for sensitive and rapid detection of trace pesticides. This study demonstrates the applicability of ink-jet printed SERS (P-SERS) substrates, fabricated from chromatography paper embedded with gold or silver nanoparticles, for quantitative SERS (qSERS) assessment of different classes of pesticides.
Test samples (malathion, arsenate, benomyl, thiram, and paraquat) were prepared by depositing dilute pesticide solutions onto the P-SERS substrates. The limit of detection for pesticides was improved drastically with P-SERS compared to normal reflective Raman, enabling the detection at concentrations as low as 1 μM. To facilitate quantitative analysis, a robust Raman model was developed to accurately predict pesticide concentrations ranging from 0.0 – 20.0 μM. The model exhibited high coefficients of determination (R2 ~ 0.96) and standard error values (SE ~ 1.3 μM) for both calibration and validation sets, affirming the quantitative potential of qSERS.
Meticulous attention to sample preparation procedures was imperative for ensuring accuracy and reproducibility. A comprehensive Standard Operating Procedure (SOP) that encompasses detailed guidelines for substrate preparation is advocated for qSERS testing; including sample application, drying, and mounting, as well as for Raman instrument operations, involving raster scanning and data collection methods. Strictly adherence to these protocols ensures consistency and reliability in results.
The proposed ink-jet printed SERS approach combined with raster scanning offers a rapid and cost-effective alternative to conventional techniques such as chromatography, mass spectrometry, and electrochemistry. Including sample preparation time, qSERS analysis can be completed in minutes, compared to other analysis methods that can take several hours. Moreover, the streamlined process minimizes consumables and waste generation, underscoring the superiority of SERS over traditional methodologies in terms of efficiency and environmental impact.
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