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

Abstract 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.