对太赫兹时域光谱用于农业食品安全检测的全面审查:通过多学科技术集成来提高传感性能
Lintong Zhang1, Shuhui Wang1,2, Wangjincheng Yang2
1Center for Artificial Intelligence in Agriculture, Fujian Agriculture and Forestry University, Fuzhou, China.
Critical reviews in analytical chemistry
|July 9, 2025
概括
太赫兹时域光谱 (THz-TDS) 与机器学习和纳米材料等先进技术相结合,显著提高了农业食品安全检测. 这种跨学科的方法改善了对物理,化学和微生物污染物的识别.
科学领域:
- 农业科学 农业科学
- 频谱学是一种光谱学.
- 材料科学 材料科学 材料科学
背景情况:
- 确保农业食品安全需要有效和准确的污染检测方法.
- 太赫兹时域光谱 (THz-TDS) 为农业食品安全提供独特的光谱特征和非破坏性分析.
- 最近的进展集中在将THz-TDS与新兴技术集成,以提高其分析能力.
研究的目的:
- 审查THz-TDS与机器学习,元材料,微流体和功能纳米材料的整合,以提高农业食品安全检测.
- 通过使用这些综合技术从2020年至2024年检测物理,化学和微生物污染物的进展情况.
- 总结目前的挑战和跨学科THz-TDS在农业食品安全中的应用的未来前景.
主要方法:
- 对 THz-TDS 集成机器学习,超材料,微流体和功能纳米材料的科学文献进行系统审查.
- 分析农业食品中的污染物 (物理,化学,微生物) 检测方面的进展.
- 评估将THz-TDS与前沿技术集成的协同效应.
主要成果:
- 将THz-TDS与机器学习 (ML) 的整合有助于破译复杂的光谱数据.
- 超材料 (MM) 增强了分析物特定的光谱特征,改善了检测.
- 功能性纳米材料 (FN) 通过吸附和等离子特性提高灵敏度和特异性;微流体 (MF) 减轻水的吸收.
- 在过去五年中,在检测各种污染物方面取得了重大进展.
结论:
- 为了在农业食品安全监测中推进THz-TDS,多学科的整合至关重要.
- 使用ML,MM,FN和MF与THz-TDS的协同作用为食品安全提供了变革性的潜力.
- 需要进一步的研究和开发来克服挑战,并充分实现集成THz-TDS系统的功能.
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