Artificial intelligence-assisted volatile and biogenic amines sensors in intelligent monitoring of food freshness-recent advances, challenges, and future prospects

IF 15.4 1区农林科学 Q1 FOOD SCIENCE & TECHNOLOGY

Trends in Food Science & Technology Pub Date : 2025-09-17 DOI:10.1016/j.tifs.2025.105319

Xiaobo Zhang, Yifan Guo, Xiuwen Wang, Jingli Yuan, Qiuyue Zheng, Bing Hu, Ronggang Liu, Jijuan Cao

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引用次数: 0

Abstract

Background

The early-stage spoilage of food during storage, transportation, and distribution poses severe threats to food safety and human health. Therefore, the development of intelligent food packaging systems integrated with freshness monitoring is of great significance. Volatile and biogenic amines (VBAs) serve as crucial indicators of food freshness. Although conventional VBAs sensors have gained widespread application, they still face challenges in terms of sensitivity, accuracy, and portability. Recently, the emergence of artificial intelligence (AI) opened new avenues for screening novel sensing materials, optimizing sensor performance, and exploring sensing mechanisms. AI shows considerable potential in developing high-performance intelligence VBAs sensors.

Scope and approach

This review comprehensively summarizes the recent advances over the past five years in AI-integrated VBAs sensors for real-time monitoring of food freshness and intelligent packaging. It primarily covers response modes of VBAs sensors, sensing materials, and their detection mechanisms. Additionally, the review highlights recent applications of smartphones integration, machine learning, wireless transmission, and self-powered systems in VBAs monitoring and intelligent food packaging. Furthermore, it discusses the current limitations of AI-assisted VBAs sensors and future perspectives.

Key findings and conclusions

AI-assisted VBAs sensors significantly enhance detection performance by processing complex multidimensional data in real-time, driving a transformative shift in food freshness detection technology from “passive monitoring” toward “intelligent decision-making”. However, it still faces challenges in device compatibility and simultaneous multi-target detection. In the future, interdisciplinary collaboration is expected to drive innovation in next-generation intelligent sensors, fostering continued progress in food safety monitoring technologies.

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人工智能辅助挥发性和生物胺传感器在食品新鲜度智能监测中的最新进展、挑战和未来前景

食品在储存、运输和流通过程中的早期变质对食品安全和人体健康构成严重威胁。因此，开发具有新鲜度监测功能的智能食品包装系统具有重要意义。挥发性胺和生物胺（VBAs）是食品新鲜度的重要指标。虽然传统的VBAs传感器已经得到了广泛的应用，但它们在灵敏度、精度和便携性方面仍然面临着挑战。近年来，人工智能（AI）的出现为筛选新型传感材料、优化传感器性能和探索传感机制开辟了新的途径。人工智能在开发高性能智能VBAs传感器方面显示出相当大的潜力。本文全面总结了过去五年来人工智能集成VBAs传感器在食品新鲜度实时监测和智能包装方面的最新进展。主要涵盖VBAs传感器的响应模式、传感材料及其检测机制。此外，该综述还强调了智能手机集成、机器学习、无线传输和自供电系统在VBAs监测和智能食品包装中的最新应用。此外，它还讨论了人工智能辅助VBAs传感器的当前局限性和未来前景。ai辅助VBAs传感器通过实时处理复杂的多维数据，显著提高了检测性能，推动了食品新鲜度检测技术从“被动监测”向“智能决策”的转型。但在设备兼容性和多目标同时检测方面仍面临挑战。未来，跨学科合作有望推动下一代智能传感器的创新，促进食品安全监测技术的持续进步。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Trends in Food Science & Technology 工程技术-食品科技

CiteScore

32.50

自引率

2.60%

发文量

322

审稿时长

37 days

期刊介绍： Trends in Food Science & Technology is a prestigious international journal that specializes in peer-reviewed articles covering the latest advancements in technology, food science, and human nutrition. It serves as a bridge between specialized primary journals and general trade magazines, providing readable and scientifically rigorous reviews and commentaries on current research developments and their potential applications in the food industry. Unlike traditional journals, Trends in Food Science & Technology does not publish original research papers. Instead, it focuses on critical and comprehensive reviews to offer valuable insights for professionals in the field. By bringing together cutting-edge research and industry applications, this journal plays a vital role in disseminating knowledge and facilitating advancements in the food science and technology sector.