A Comprehensive Review of Terahertz Time-Domain Spectroscopy for Agri-Food Safety Detection: Enhanced Sensing Performance Through Multidisciplinary Technology Integration

Abstract

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.