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Ahmed Filayih Hassan
Education Directorate of Dhi Qar

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Sensitive Food Pesticide Analysis Using Silver Nanostructured Raman Substrates Ahmed Filayih Hassan
Academia Open Vol. 10 No. 2 (2025): December
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/acopen.10.2025.12933

Abstract

General Background: Pesticide residues in food remain a global safety concern, requiring analytical methods that are both rapid and highly sensitive. Specific Background: Conventional chromatographic techniques provide accurate detection but are limited by high cost, long processing times, and complex sample preparation, restricting routine monitoring. Knowledge Gap: Despite growing interest in Surface-Enhanced Raman Scattering (SERS), challenges persist regarding substrate reproducibility, sensitivity across diverse food matrices, and validation against regulatory standards. Aims: This study aimed to develop, optimize, and validate nanostructured silver SERS substrates for the sensitive detection of organophosphorus and organochlorine pesticides in food. Results: The fabricated substrates achieved enhancement factors above 10⁸, detection limits as low as 0.05–0.1 ng/mL, strong linearity, high reproducibility, and accurate recovery across apple juice, tomato extract, and rice samples. Analytical performance showed strong agreement with GC-MS while reducing total analysis time to under 15 minutes. Novelty: The work integrates controlled nanoparticle aggregation with optimized sample-matrix handling, yielding highly reproducible, stable, and field-ready SERS substrates. Implications: The findings demonstrate a practical and cost-effective platform for high-throughput pesticide monitoring, with potential for portable on-site food safety assessment and future expansion to broader contaminant classes.Highlight : Silver-based SERS substrates provide very high-sensitivity pesticide detection. The method offers much faster analysis than conventional techniques. It works effectively across multiple food matrices. Keywords : SERS, silver nanoparticles, pesticide detection, food safety, surface enhancement, Raman spectroscopy