农产品中新烟碱类农药残留快速检测技术研究进展

Research Progress in Rapid Detection Technologies of Neonicotinoid Pesticide Residues in Agricultural Products

摘要:

新烟碱类农药（neonicotinoid pesticides，NEOs）凭借高效、广谱、低毒和低残留等优势，在全球农业生产中得到广泛应用。但该类农药若被不当使用，会对生态环境造成污染，同时对人类健康构成严重威胁。因此，研发具备现场适用性、高通量特征的新型快速检测技术已成为当前的研究焦点。作者综述了NEOs残留快速检测技术的检测原理、优势与局限性，详细介绍了酶联免疫吸附测定、荧光免疫分析、免疫层析、表面等离子体共振（SPR）、表面增强拉曼散射（SERS）、荧光共振能量转移（FRET）、分子印迹技术（MIT）、金属有机框架材料（MOTs）和纳米材料电化学传感器等在农产品中NEOs残留检测中的研究进展。以免疫分析、光学分析、电化学分析为代表的农药残留检测技术凭借其高灵敏性、高选择性等优点，在痕量NEOs残留的快速检测中展现出巨大应用潜力，但在检测限降低、灵敏度提升和基质干扰消除等方面仍存在不足。未来在实际检测应用中，应重点围绕消除基质效应、实现智能化和自动化、推进多功能集成等方向进行创新与优化。

Abstract:

Neonicotinoid pesticides (NEOs) are widely used in global agricultural production because of their high efficiency, broad spectra, low toxicity, and low residues. However, improper use of NEOs will cause environmental pollution and pose a serious threat to human health. Therefore, developing new rapid detection technologies with field applicability and high throughput has become the focus of current research. The author reviewed the principles, advantages, and limitations of rapid detection technologies of neonicotinoid pesticide residues, and introduced in detail enzyme-linked immunosorbent assay, fluorescence immunoassay, immunochromatography, surface plasma resonance (SPR), surface-enhanced Raman scattering (SERS), fluorescence resonance energy transfer (FRET), molecular imprinting (MIT), and electrochemical sensors based on metal-organic frameworks (MOTs) and nanomaterials in the detection of neonicotinoid pesticide residues in agricultural products. With high sensitivity and high selectivity, the pesticide residue detection technologies represented by immunoassay, optical analysis, and electrochemical detection demonstrate great potential for the rapid detection of trace neonicotinoid pesticide residues, while they still have certain limitations in terms of detection limits, sensitivity, matrix treatment, etc. In the future practical testing, attention should be paid to the innovation and optimization in matrix effect elimination, intelligence and automation, and multi-functional integration.