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Review highlights non-noble metal SERS substrates that improve food safety by detecting pesticide residues and heavy metal pollutants.
Food safety concerns are becoming increasingly critical, as trace contaminants such as antibiotic and pesticide residues, illicit additives, synthetic colorants, and heavy metal pollutants pose significant risks to human health. Developing rapid, sensitive, and cost-effective strategies for detecting these substances in complex food matrices has therefore become a pressing challenge in food safety monitoring. This review specifically focuses on food contaminants, including antibiotic and pesticide residues, illegal additives, synthetic colorants, and heavy-metal pollutants—that directly threaten food safety. Surface-enhanced Raman scattering (SERS), with its molecular fingerprinting capability and ultrahigh sensitivity, is widely regarded as a promising technique for this purpose. Nevertheless, the practical deployment of noble-metal substrates has been limited by high cost, poor stability, and reproducibility issues. In response, non-noble-metal SERS substrates have recently attracted substantial attention as viable alternatives. Their enhancement is dominated by chemical mechanisms (CM), where charge transfer (CT), defect-state modulation, and heterostructure coupling act synergistically to achieve signal amplification. Representative materials, including metal oxides, transition-metal chalcogenides, carbon-based systems, and emerging two-dimensional or hybrid structures, have exhibited distinct advantages in the trace detection of diverse food contaminants. This review systematically summarizes enhancement mechanisms, material categories, performance-optimization strategies, and recent advances in the field. It further highlights current challenges related to quantitative mechanistic understanding, substrate stability, matrix interference, and lack of standardized protocols. Finally, future directions are outlined, focusing on theory-guided material design, innovations in multimodal detection, and the development of portable sensing platforms, thereby offering systematic reference and scientific guidance for both fundamental research and practical translation.
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Ge et al. (2025) studied this question.
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