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Metal-polyphenol Multistage Competitive Coordination System for Colorimetric Monitoring Meat Freshness

Journal 2025 · IF 26.8 · 发表于 2025 年 4 月 1 日
作者: Jun Cheng,Yao Shen,Yulu Gu,Tongyue Xiang,Hui Shen,Yi Wang,Zhenyang Hu,Zhen Zheng,Zhilong Yu,Qin Wu,Yinghui Wang,Tiancong Zhao,Yunfei Xie
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摘要

A low-cost, high-precision, and secure real-time system for monitoring food freshness can significantly improve spoilage issues, yet traditional colorimetric sensor arrays often suffer from chemical dyes’ high toxicity and limited color changes. Here, a metal-polyphenol network colorimetric sensor array (MPN-CSA) is built for detecting total volatile base nitrogen (TVB-N) markers of meat freshness. The multi-level competitive coordination process between the metal-polyphenol system and amine substances endows the system with color changes far beyond those of traditional dyes (reaching a detection limit of 300 ppb). By integrating convolutional neural network (CNN) technology, an online platform is developed for monitoring meat freshness, achieving an overall detection accuracy rate of 99.83%. This environmentally friendly, economically viable MPN-CSA that monitors the freshness of meat in complex storage environments can be incorporated into food packaging boxes, enabling consumers and suppliers to assess the freshness of meat in real-time, thus helping to reduce food waste and prevent foodborne illnesses.

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