光学农药检测阵列中的传感元件设计

摘要(中文译文)

全球对合成农药的依赖日益加剧，以保障农业生产力，这加剧了人们对其对人类健康和生态系统不利影响的担忧。农药暴露与严重病理相关，包括神经毒性、内分泌干扰和致癌作用，因此迫切需要快速、灵敏且可现场部署的监测工具。传统分析方法如气相或液相色谱-质谱联用具有高准确性，但由于成本高、操作复杂且对基础设施要求高，不适用于现场实时筛查。为此，光学（生物）传感器阵列已成为强有力的替代方案，其通过交叉反应性传感元件集合产生多维响应模式（分析物特异性指纹），模拟生物感官系统。本综述对用于农药检测的此类阵列中关键传感元件类别进行了全面且机制驱动的分析，包括无标记等离激元纳米颗粒、化学传感器、主客体系统、酶、抗体和适配体。本综述批判性评估了每种平台的工作原理、最新进展、实际局限性和现实适用性。通过在统一的概念框架下整合多样化的传感范式，本综述从已报道的光学传感器阵列中提炼出关键设计原则，并为设计用于检测和区分农药残留的实用平台提供了可操作的指导——在稳健性、简便性和可扩展性之间取得平衡，以适用于现实世界的环境与食品安全应用。

Abstract

The escalating global reliance on synthetic pesticides to secure agricultural productivity has intensified concerns over their adverse impacts on human health and ecosystems. With pesticide exposure linked to severe pathologies-including neurotoxicity, endocrine disruption, and carcinogenesis-there is an urgent need for rapid, sensitive, and field-deployable monitoring tools. Conventional analytical methods such as gas or liquid chromatography coupled with mass spectrometry offer high accuracy but are impractical for on-site, real-time screening due to their cost, complexity, and infrastructure demands. In response, optical (bio)sensor arrays have emerged as powerful alternatives that mimic biological sensory systems by generating multidimensional response patterns (analyte-specific fingerprints) from ensembles of cross-reactive sensing elements. This review provides a comprehensive and mechanism-driven analysis of the key sensing element classes used in these arrays for pesticide detection, including label-free plasmonic nanoparticles, chemosensors, host-guest systems, enzymes, antibodies, and aptamers. This review critically evaluates the operational principles, recent advances, practical limitations, and real-world applicability of each platform. By unifying diverse sensing paradigms under a common conceptual framework, this review distills key design principles from reported optical sensor arrays and provides actionable guidance for designing practical platforms to detect and discriminate pesticide residues-balancing robustness, simplicity, and scalability for real-world environmental and food safety applications.

如何引用

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