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AI‐based R&D for frozen and thawed meat: Research progress and future prospects

计算机科学 持续性 个性化 质量(理念) 生产(经济) 业务 生物技术 生物 生态学 认识论 万维网 哲学 宏观经济学 经济
作者
Jiangshan Qiao,Min Zhang,Dayuan Wang,Arun S. Mujumdar,Chaoyang Chu
出处
期刊:Comprehensive Reviews in Food Science and Food Safety [Wiley]
卷期号:23 (5): e70016-e70016 被引量:9
标识
DOI:10.1111/1541-4337.70016
摘要

Abstract Frozen and thawed meat plays an important role in stabilizing the meat supply chain and extending the shelf life of meat. However, traditional methods of research and development (R&D) struggle to meet rising demands for quality, nutritional value, innovation, safety, production efficiency, and sustainability. Frozen and thawed meat faces specific challenges, including quality degradation during thawing. Artificial intelligence (AI) has emerged as a promising solution to tackle these challenges in R&D of frozen and thawed meat. AI's capabilities in perception, judgment, and execution demonstrate significant potential in problem‐solving and task execution. This review outlines the architecture of applying AI technology to the R&D of frozen and thawed meat, aiming to make AI better implement and deliver solutions. In comparison to traditional R&D methods, the current research progress and promising application prospects of AI in this field are comprehensively summarized, focusing on its role in addressing key challenges such as rapid optimization of thawing process. AI has already demonstrated success in areas such as product development, production optimization, risk management, and quality control for frozen and thawed meat. In the future, AI‐based R&D for frozen and thawed meat will also play an important role in promoting personalization, intelligent production, and sustainable development. However, challenges remain, including the need for high‐quality data, complex implementation, volatile processes, and environmental considerations. To realize the full potential of AI that can be integrated into R&D of frozen and thawed meat, further research is needed to develop more robust and reliable AI solutions, such as general AI, explainable AI, and green AI.
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