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

IF 12 1区 农林科学 Q1 FOOD SCIENCE & TECHNOLOGY Comprehensive Reviews in Food Science and Food Safety Pub Date : 2024-09-08 DOI:10.1111/1541-4337.70016
Jiangshan Qiao, Min Zhang, Dayuan Wang, Arun S. Mujumdar, Chaoyang Chu
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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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基于人工智能的冻肉和解冻肉研发:研究进展与未来展望。
冷冻和解冻肉类在稳定肉类供应链和延长肉类保质期方面发挥着重要作用。然而,传统的研发(R&D)方法难以满足人们在质量、营养价值、创新、安全、生产效率和可持续性等方面日益增长的需求。冷冻和解冻肉类面临着特殊的挑战,包括解冻过程中的质量下降。人工智能(AI)已成为应对冷冻和解冻肉类研发挑战的一种前景广阔的解决方案。人工智能在感知、判断和执行方面的能力显示了其在解决问题和执行任务方面的巨大潜力。本综述概述了将人工智能技术应用于冷冻和解冻肉类研发的架构,旨在让人工智能更好地实施和提供解决方案。与传统研发方法相比,本综述全面总结了人工智能在该领域的研究进展和应用前景,重点介绍了人工智能在解决解冻过程快速优化等关键挑战方面的作用。人工智能已在冻肉和解冻肉的产品开发、生产优化、风险管理和质量控制等领域取得了成功。未来,基于人工智能的冻肉和解冻肉研发还将在促进个性化、智能化生产和可持续发展方面发挥重要作用。然而,挑战依然存在,包括对高质量数据的需求、复杂的实施、不稳定的流程和环境因素。为了充分发挥人工智能在冷冻和解冻肉类研发中的潜力,需要进一步研究开发更强大、更可靠的人工智能解决方案,如通用人工智能、可解释人工智能和绿色人工智能。
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来源期刊
CiteScore
26.20
自引率
2.70%
发文量
182
期刊介绍: Comprehensive Reviews in Food Science and Food Safety (CRFSFS) is an online peer-reviewed journal established in 2002. It aims to provide scientists with unique and comprehensive reviews covering various aspects of food science and technology. CRFSFS publishes in-depth reviews addressing the chemical, microbiological, physical, sensory, and nutritional properties of foods, as well as food processing, engineering, analytical methods, and packaging. Manuscripts should contribute new insights and recommendations to the scientific knowledge on the topic. The journal prioritizes recent developments and encourages critical assessment of experimental design and interpretation of results. Topics related to food safety, such as preventive controls, ingredient contaminants, storage, food authenticity, and adulteration, are considered. Reviews on food hazards must demonstrate validity and reliability in real food systems, not just in model systems. Additionally, reviews on nutritional properties should provide a realistic perspective on how foods influence health, considering processing and storage effects on bioactivity. The journal also accepts reviews on consumer behavior, risk assessment, food regulations, and post-harvest physiology. Authors are encouraged to consult the Editor in Chief before submission to ensure topic suitability. Systematic reviews and meta-analyses on analytical and sensory methods, quality control, and food safety approaches are welcomed, with authors advised to follow IFIS Good review practice guidelines.
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