数字农科院2.0

Intelligent food preservation systems based on MOFs-AI integration: technological breakthroughs and developmental trends

文献类型： 外文期刊

作者： Ding, Xin;Ai, Nasi;Zhao, Yiming;Li, Lingyun;Chen, Ge;Xu, Donghui;Xu, Xiaomin;Qin, Lin;Chen, Jing;Liu, Guangyang

作者机构：

关键词： Metal-organic framework;Artificial intelligence;Intelligent food preservation;AI-guided synthesis strategies;Structure-performance relationship

期刊名称： FOOD CHEMISTRY

ISSN： 0308-8146

年卷期： 2025 年 498 卷

页码：

收录情况： SCIE（2025版） ; ; EI（2025版）

摘要： Intelligent preservation systems incorporating functional nanomaterials exhibit extensive applicability and present favorable development trends. Metal-organic frameworks (MOFs), novel porous crystalline materials, demonstrate exceptional gas adsorption, controlled release, and environmental responsiveness due to their ultrahigh surface area, tunable pores, and versatile functionalization. MOFs have shown considerable potential in intelligent food preservation applications through their integration with artificial intelligence (AI) technologies as emerging nanomaterials. It enables comprehensive innovation spanning from molecular-level material design to intelligent terminal packaging, demonstrating significant interdisciplinary value. This review examines novel AI-guided synthesis strategies for MOFs and systematically reviews their structural characteristics and classification schemes. This review systematically analyzes how MOFs structural parameters-metal ions, pore architecture, and loading capacity-govern antimicrobial, gas/humidity regulation, and stimulus-responsive properties in intelligent preservation. Furthermore, this work presents a comprehensive review of recent advances in MOFbased intelligent food preservation, while thoroughly demonstrating the significant potential of MOFs-AI integration for next-generation intelligent preservation technologies.

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