Application of machine learning in intelligent fish aquaculture: A review

• Published in: Aquaculture Vol. 540; p. 736724
• Main Authors: Zhao, Shili, Zhang, Song, Liu, Jincun, Wang, He, Zhu, Jia, Li, Daoliang, Zhao, Ran
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 15-07-2021
• Subjects: Fish aquaculture; Fishery development; Machine learning; Fishery development; Machine learning; Fish aquaculture
• ISSN: 0044-8486; 1873-5622
• DOI: 10.1016/j.aquaculture.2021.736724

Among the background of developments in automation and intelligence, machine learning technology has been extensively applied in aquaculture in recent years, providing a new opportunity for the realization of digital fishery farming. In the present paper, the machine learning algorithms and techniques adopted in intelligent fish aquaculture in the past five years are expounded, and the application of machine learning in aquaculture is explored in detail, including the information evaluation of fish biomass, the identification and classification of fish, behavioral analysis and prediction of water quality parameters. Further, the application of machine learning algorithms in aquaculture is outlined, and the results are analyzed. Finally, several current problems in aquaculture are highlighted, and the development trend is considered.
•Expounde the machine learning algorithms and techniques in intelligent fish aquaculture in the past five years.•Explore the application of machine learning in aquaculture, including the information evaluation of fish biomass, the identification and classification of fish, behavioral analysis and prediction of water quality parameters.•Analyze the results of the application of machine learning algorithms in aquaculture.