多学科方法
太赫兹辐射
食品安全
纳米技术
领域(数学分析)
光谱学
材料科学
计算机科学
工艺工程
环境科学
光电子学
工程类
物理
化学
食品科学
数学
政治学
数学分析
量子力学
法学
作者
Lintong Zhang,Shuhui Wang,Weiling Yang,Xinze Liu,Zenghui Wei,Alwaseela Abdalla,Jia‐Chen Zhang,Xiangzeng Kong,Fangfang Qu
标识
DOI:10.1080/10408347.2025.2527748
摘要
The development of efficient and accurate methods for detecting contamination in agri-foods is critical for ensuring food safety. Terahertz time-domain spectroscopy (THz-TDS), distinguished by its unique spectral characteristics and nondestructive detection capabilities, emerges as a powerful tool for analyzing agri-food safety. This review systematically examines the integration of THz-TDS with frontier technologies (machine learning [ML], metamaterials [MM], microfluidics [MF], and functional nanomaterials [FN]) to enhance detection capabilities. The article delves into the advancements achieved in detecting physical, chemical, and microbial contaminants in agri-food over the past five years (2020-2024) through the integration of THz-TDS with these frontier technologies. Based on the current state of research, this article summarizes the challenges and prospects of THz-TDS with interdisciplinary integration technologies in applications. To advance THz-TDS for agri-food safety monitoring, multidisciplinary integration is required. ML is critical for deciphering complex THz spectral datasets, while MM play a pivotal role in amplifying analyte-specific spectral signatures. FN leverage their potential high-throughput specific adsorption and plasmonic resonance properties to enhance detection sensitivity and specificity. The MF systems can reduce absorption induced by water. This review aims to provide new insights into the multidisciplinary convergence to propel THz-TDS toward transformative agri-food safety applications.
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