Peihua Ma , Shawn Tsai , Yiyang He , Xiaoxue Jia , Dongyang Zhen , Ning Yu , Qin Wang , Jaspreet K.C. Ahuja , Cheng-I Wei
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Challenges like data biases, misinformation risks, and implementation hurdles, including data limitations and ethical concerns, are discussed. The necessity for interdisciplinary collaboration to overcome these challenges is also highlighted.</p></div><div><h3>Key findings and conclusions</h3><p>LLMs hold significant potential in automating processes and improving accuracy and efficiency in the global food system. Successful implementation requires continuous updates and ethical considerations. The paper provides insights for academics, industry professionals, and policymakers on the impact of LLMs in food science, emphasizing the importance of interdisciplinary efforts in this domain. Despite potential challenges, the integration of LLMs in food science promises transformative advancements.</p></div>","PeriodicalId":441,"journal":{"name":"Trends in Food Science & Technology","volume":null,"pages":null},"PeriodicalIF":15.1000,"publicationDate":"2024-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Large language models in food science: Innovations, applications, and future\",\"authors\":\"Peihua Ma , Shawn Tsai , Yiyang He , Xiaoxue Jia , Dongyang Zhen , Ning Yu , Qin Wang , Jaspreet K.C. Ahuja , Cheng-I Wei\",\"doi\":\"10.1016/j.tifs.2024.104488\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Background</h3><p>Large Language Models (LLMs) are increasingly significant in food science, transforming areas such as recipe development, nutritional analysis, food safety, and supply chain management. These models bring sophisticated decision-making, predictive analytics, and natural language processing capabilities to various aspects of food science.</p></div><div><h3>Scope and approach</h3><p>The review focuses on the application of LLMs in enhancing food science, with a strong emphasis on food safety, especially in contaminant detection and risk assessment. It addresses the roles of AI and LLMs in regulatory compliance and food quality control. Challenges like data biases, misinformation risks, and implementation hurdles, including data limitations and ethical concerns, are discussed. The necessity for interdisciplinary collaboration to overcome these challenges is also highlighted.</p></div><div><h3>Key findings and conclusions</h3><p>LLMs hold significant potential in automating processes and improving accuracy and efficiency in the global food system. Successful implementation requires continuous updates and ethical considerations. The paper provides insights for academics, industry professionals, and policymakers on the impact of LLMs in food science, emphasizing the importance of interdisciplinary efforts in this domain. Despite potential challenges, the integration of LLMs in food science promises transformative advancements.</p></div>\",\"PeriodicalId\":441,\"journal\":{\"name\":\"Trends in Food Science & Technology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":15.1000,\"publicationDate\":\"2024-04-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Trends in Food Science & Technology\",\"FirstCategoryId\":\"97\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S092422442400164X\",\"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":"Trends in Food Science & Technology","FirstCategoryId":"97","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S092422442400164X","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}
Large language models in food science: Innovations, applications, and future
Background
Large Language Models (LLMs) are increasingly significant in food science, transforming areas such as recipe development, nutritional analysis, food safety, and supply chain management. These models bring sophisticated decision-making, predictive analytics, and natural language processing capabilities to various aspects of food science.
Scope and approach
The review focuses on the application of LLMs in enhancing food science, with a strong emphasis on food safety, especially in contaminant detection and risk assessment. It addresses the roles of AI and LLMs in regulatory compliance and food quality control. Challenges like data biases, misinformation risks, and implementation hurdles, including data limitations and ethical concerns, are discussed. The necessity for interdisciplinary collaboration to overcome these challenges is also highlighted.
Key findings and conclusions
LLMs hold significant potential in automating processes and improving accuracy and efficiency in the global food system. Successful implementation requires continuous updates and ethical considerations. The paper provides insights for academics, industry professionals, and policymakers on the impact of LLMs in food science, emphasizing the importance of interdisciplinary efforts in this domain. Despite potential challenges, the integration of LLMs in food science promises transformative advancements.
期刊介绍:
Trends in Food Science & Technology is a prestigious international journal that specializes in peer-reviewed articles covering the latest advancements in technology, food science, and human nutrition. It serves as a bridge between specialized primary journals and general trade magazines, providing readable and scientifically rigorous reviews and commentaries on current research developments and their potential applications in the food industry.
Unlike traditional journals, Trends in Food Science & Technology does not publish original research papers. Instead, it focuses on critical and comprehensive reviews to offer valuable insights for professionals in the field. By bringing together cutting-edge research and industry applications, this journal plays a vital role in disseminating knowledge and facilitating advancements in the food science and technology sector.