Yang Jie, Bai Xue, Wei Mingji, Jiang Hui, Xu Leijun
School of Electrical and Information Engineering, Jiangsu University, Zhenjiang 212013, China.
Foods. 2025 Jun 23;14(13):2199. doi: 10.3390/foods14132199.
Terahertz spectroscopy (0.1~10 THz), as a new type of non-destructive testing method with both microwave and infrared characteristics, has shown remarkable potential in the field of food quality testing in recent years. Its unique penetration, high sensitivity, and low photon energy characteristics, combined with chemometrics and machine learning methods, provide an efficient solution for the qualitative and quantitative analysis of complex food ingredients. In this paper, we systematically review the principles of terahertz spectroscopy and its key applications in food testing, focusing on its research progress in pesticide residues, additives, biotoxins, and mold, adulteration identification, variety identification, and nutrient content detection. By integrating spectral data preprocessing, reconstruction algorithms, and machine learning model optimization strategies, this paper further analyzes the advantages and challenges of this technology in enhancing detection accuracy and efficiency. In addition, combined with the urgent demand for fast and nondestructive technology in the field of food detection, the future development direction of the deep integration of terahertz spectroscopy technology and artificial intelligence is envisioned, with a view to providing theoretical support and technical reference for food safety assurance and nutritional health research.
太赫兹光谱(0.1~10太赫兹)作为一种兼具微波和红外特性的新型无损检测方法,近年来在食品质量检测领域展现出了巨大潜力。其独特的穿透性、高灵敏度和低光子能量特性,与化学计量学和机器学习方法相结合,为复杂食品成分的定性和定量分析提供了一种高效解决方案。本文系统综述了太赫兹光谱的原理及其在食品检测中的关键应用,重点关注其在农药残留、添加剂、生物毒素、霉菌、掺假鉴定、品种鉴定和营养成分检测方面的研究进展。通过整合光谱数据预处理、重建算法和机器学习模型优化策略,本文进一步分析了该技术在提高检测准确性和效率方面的优势与挑战。此外,结合食品检测领域对快速无损技术的迫切需求,展望了太赫兹光谱技术与人工智能深度融合的未来发展方向,以期为食品安全保障和营养健康研究提供理论支持和技术参考。