Intelligent feeding technique based on predicting shrimp growth in recirculating aquaculture system

doi:10.1111/are.15938

IOCAS-IR > 实验海洋生物学重点实验室

	Intelligent feeding technique based on predicting shrimp growth in recirculating aquaculture system
	Chen, Fudi1,2,3 ; Sun, Ming1,2,3 ; Du, Yishuai 1,2; Xu, Jianping 1,2; Zhou, Li 1,2; Qiu, Tianlong1,2 ; Sun, Jianming 1,2
	2022-06-22
发表期刊	AQUACULTURE RESEARCH
ISSN	1355-557X
页码	13
通讯作者	Sun, Jianming([email protected])
摘要	Precise feeding in the recirculating aquaculture mode is a critical scientific problem that urgently needs a solution. This study aimed to develop an intelligent feeding technique in a recirculating aquaculture system for rearing Litopenaeus vannamei. The core of the intelligent feeding technique is the shrimp biomass prediction model. Accurate prediction of shrimp biomass could determine the appropriate feeding amount and ensure stable water quality. The data-driven prediction model was developed based on water quality indicators and aquaculture management data collected during shrimp rearing. Multiple linear regression, artificial neural networks and a support vector machine (SVM) were introduced to develop the shrimp biomass predicting model. Results showed that the SVM model gave the lowest root mean square error (0.6500), mean absolute error (0.4368) and mean absolute percentage error (3.70%), as well as the highest accuracy (90.91%). By analysing the predictive ability of the machine learning models, it was determined that the SVM model was the optimal model for predicting biomass. The intelligent feeding machine can apply the optimal model to calculate the shrimp biomass and determine the appropriate feeding amount by reading the sensors in real time.
关键词	Litopenaeus vannamei precise feeding predicting model shrimp biomass
DOI	10.1111/are.15938
收录类别	SCI
语种	英语
资助项目	China Postdoctoral Science Foundation[2021M693212]; Ministry of Science and Technology of the People's Republic of China[2017YFE0118300]; Ministry of Science and Technology of the People's Republic of China[2019YFD0900502]; Ministry of Science and Technology of the People's Republic of China[2019YFD0900800]
WOS研究方向	Fisheries
WOS类目	Fisheries
WOS记录号	WOS:000814051300001
出版者	WILEY
引用统计	被引频次：7[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.qdio.ac.cn/handle/337002/179605
专题	实验海洋生物学重点实验室
通讯作者	Sun, Jianming
作者单位	1.Chinese Acad Sci, Ctr Ocean Megasci, Inst Oceanol, CAS & Shandong Prov Key Lab Expt Marine Biol, Qingdao 266071, Peoples R China 2.Qingdao Natl Lab Marine Sci & Technol, Lab Marine Biol & Biotechnol, Qingdao, Peoples R China 3.Liaoning Ocean & Fisheries Sci Res Inst, Liaoning Prov Key Lab Marine Biol Resources & Eco, Dalian Key Lab Conservat Fishery Resources, Dalian, Peoples R China
第一作者单位	中国科学院海洋大科学研究中心
通讯作者单位	中国科学院海洋大科学研究中心
推荐引用方式 GB/T 7714	Chen, Fudi,Sun, Ming,Du, Yishuai,et al. Intelligent feeding technique based on predicting shrimp growth in recirculating aquaculture system[J]. AQUACULTURE RESEARCH,2022:13.
APA	Chen, Fudi.,Sun, Ming.,Du, Yishuai.,Xu, Jianping.,Zhou, Li.,...&Sun, Jianming.(2022).Intelligent feeding technique based on predicting shrimp growth in recirculating aquaculture system.AQUACULTURE RESEARCH,13.
MLA	Chen, Fudi,et al."Intelligent feeding technique based on predicting shrimp growth in recirculating aquaculture system".AQUACULTURE RESEARCH (2022):13.