数字农科院2.0

AI awakens food packaging: Integrative advances, challenges, and future perspectives

文献类型： 外文期刊

作者： Jia, Xiaoxue;Li, Xiaoan;Alharbi, Mazen O.;Ma, Peihua;Ismail-Fitry, Mohammad Rashedi;Xia, Shuangmei;Zhang, Ya;Li, Yi;Wang, Qin

作者机构：

关键词： Artificial intelligence;Food packaging;Food safety;Packaging design;Sustainability

期刊名称： TRENDS IN FOOD SCIENCE & TECHNOLOGY

ISSN： 0924-2244

年卷期： 2025 年 168 卷

页码：

收录情况： SCIE（2025版） ; ; EI（2025版）

摘要： Background: Growing concerns about food safety, environmental sustainability, and consumer expectations are driving the transition from conventional passive packaging to active systems. Artificial intelligence (AI) has emerged as a transformative tool to enhance food packaging by enabling data-driven design, real-time monitoring, and predictive quality control, thereby reducing food waste and supporting circular economy goals. Scope and approach: This review provides a comprehensive and integrative analysis of AI-enabled innovations in food packaging. It introduces key AI technologies-including machine learning, deep learning, and generative models-and explores their applications across nine critical domains: material design and optimization, food safety and freshness monitoring, chemical migration and toxicity prediction, packaging process automation, supply chain and logistics optimization, personalized packaging design, recycling and waste reduction, carbon footprint assessment, and information and traceability systems. In addition, this review identifies the main technical, regulatory, economic, and consumer-related challenges and proposes future research directions to guide the transition from laboratory research to commercial implementation. Key findings and conclusions: AI has demonstrated exceptional potential to improve packaging material performance, enable intelligent spoilage and quality monitoring, ensure chemical safety, and optimize manufacturing and supply chains. However, barriers such as limited data availability, complex regulatory requirements, high implementation costs, and the need for greater consumer trust remain significant. Future research should prioritize developing advanced materials for complex food systems, biodegradable and recyclable sensor platforms, interpretable and energy-efficient AI models, standardized evaluation frameworks, and strategies for economic feasibility and consumer engagement. Overall, AI-enabled intelligent packaging offers a promising pathway to achieving safe, smart, and sustainable food systems.

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