文献类型： 外文期刊
作者： Li, Penglong 1 ; Han, Haibin 1 ; Zhang, Shengmao 1 ; Fang, Hui 1 ; Fan, Wei 1 ; Zhao, Feng 1 ; Xu, Chaofei 3 ;
作者机构： 1.Chinese Acad Fishery Sci, East China Sea Fisheries Res Inst, Key Lab Fisheries Remote Sensing Minist Agr & Rura, Shanghai 200090, Peoples R China
2.Dalian Ocean Univ, Sch Nav & Naval Architecture, Dalian 116023, Peoples R China
3.Suzhou Jiean Informat Technol Co Ltd, Suzhou 215004, Peoples R China
关键词： Aquaculture; Precision feeding systems; Digitization; Intelligence
期刊名称：AQUACULTURE INTERNATIONAL （ 影响因子：2.4； 五年影响因子：2.7 ）
ISSN： 0967-6120
年卷期： 2025 年 33 卷 3 期
页码：
收录情况： SCI
摘要： The digital transformation of China's traditional aquaculture industry has promoted the high-quality development of China's aquaculture industry and helped China become one of the world's largest aquaculture countries. In this paper, the current status of aquaculture digital transformation will be described from two perspectives: aquaculture process and aquaculture digital technology. The aquaculture process can be divided into eight steps by the eight-step intensive aquaculture method, and each aquaculture step and aquaculture digital intelligence technology are analyzed, revealing that technologies such as the Internet of Things (IoT), cloud computing, artificial intelligence, etc. promote high-speed growth of aquaculture productivity through the adjustment of aquaculture management decisions and the improvement of production factors, and that big data and blockchain technologies contribute to building a more trustworthy environment for online transactions and improving product traceability, offering potential steps toward integrated aquaculture. This review summarizes successful cases of digital transformation in Chinese aquaculture, providing a reference for the future development of digital aquaculture in the world. This review draws on the successful experience of China's aquaculture transformation to help accelerate the adoption of digital intelligence in aquaculture plants around the world and to serve as a basis for the improvement of current and future digital intelligence technologies.
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