Jiangshan Qiao, Min Zhang, Dayuan Wang, Arun S. Mujumdar, Chaoyang Chu
{"title":"基于人工智能的冻肉和解冻肉研发:研究进展与未来展望。","authors":"Jiangshan Qiao, Min Zhang, Dayuan Wang, Arun S. Mujumdar, Chaoyang Chu","doi":"10.1111/1541-4337.70016","DOIUrl":null,"url":null,"abstract":"<p>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.</p>","PeriodicalId":155,"journal":{"name":"Comprehensive Reviews in Food Science and Food Safety","volume":"23 5","pages":""},"PeriodicalIF":12.0000,"publicationDate":"2024-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"AI-based R&D for frozen and thawed meat: Research progress and future prospects\",\"authors\":\"Jiangshan Qiao, Min Zhang, Dayuan Wang, Arun S. Mujumdar, Chaoyang Chu\",\"doi\":\"10.1111/1541-4337.70016\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>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.</p>\",\"PeriodicalId\":155,\"journal\":{\"name\":\"Comprehensive Reviews in Food Science and Food Safety\",\"volume\":\"23 5\",\"pages\":\"\"},\"PeriodicalIF\":12.0000,\"publicationDate\":\"2024-09-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Comprehensive Reviews in Food Science and Food Safety\",\"FirstCategoryId\":\"97\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1111/1541-4337.70016\",\"RegionNum\":1,\"RegionCategory\":\"农林科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"FOOD SCIENCE & TECHNOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Comprehensive Reviews in Food Science and Food Safety","FirstCategoryId":"97","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/1541-4337.70016","RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"FOOD SCIENCE & TECHNOLOGY","Score":null,"Total":0}
AI-based R&D for frozen and thawed meat: Research progress and future prospects
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.
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.