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水产养殖智能投饵技术研究进展

Research Progress of Intelligent Feeding Technology in Aquaculture
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摘要 在水产养殖中,投喂成本占总养殖成本的40%~80%,是影响水产养殖效益的主要因素。因此,如何做到科学投喂是降低养殖成本、增加养殖经济效益的关键。智能投饵就是利用各类传感器获取鱼群摄食过程中的全局信息,结合相关算法与模型将信息反馈给控制系统动态调整投饵策略的投喂方式,是做到科学投喂、提高配合饲料利用率的有效手段。近年来,水产养殖智能投饵研究取得了一定成果,但由于实际养殖存在诸多不确定因素,实现智能投饵仍面临挑战。文章介绍了自动投饵机与自动投饵系统的研究现状,主要综述了基于机器视觉、声学、水质参数和生物模型等技术的智能投饵方法,指出了各方法的优缺点并进行总结。今后,应加强对水产养殖动物摄食过程中的图像、声音、环境因子、生物模型等信息的综合分析与运用,以提高智能投饵系统对摄食强度评估的准确性以及与养殖环境的匹配度。 In aquaculture,the cost of feeding is the main factor affecting the efficiency of breed-ing,accounting for 40 to 80 percent of the total cost.Therefore,how to do scientific feeding is the key to reducing the cost of breeding and increase the economic benefits of breeding.Intelligent feed-ing is a feeding method of using all kinds of sen-sors to get the global information in the process of feeding,and combining with the relevant algorithm and model,the information is fed back to the control system to adjust the feeding strategy.It is also an effective means to achieve scientific feeding and im-prove efficiency.In recent years,some achievements have been made in the research of intelligent feed-ing in aquaculture,but there are still challenges in the realization of intelligent feeding due to many un-certain factors in aquaculture.The research status of automatic feeding machine and automatic feeding system is introduced.The intelligent feeding methods based on machine vision,acoustics,water quality parameters and biological model are summarized,the advantages and disadvantages of these methods are also summarized.In the future,in order to improve the accuracy of feeding intensity assessment and the adaptability of the intelligent feeding system to the breeding environment,we should strengthen the com-prehensive analysis and application of the information such as image,voice,environmental factors and biological models in the process of fish feeding.
作者 雷高辉 刘峰 董小宁 杜壮壮 马意民 LEI Gaohui;LIU Feng;DONG Xiaoning;DU Zhuangzhuang;MA Yimin(Yantai Institute of China Agricultural University,Shandong Yantai 264670,China;College of Engineering,China Agricultural University,Beijing 100083,China;Yantai Engineering&Technology College,Shandong Yantai 264670,China;College of Information and Electrical Engineering,China Agricultural University,Beijing 100083,China)
出处 《饲料工业》 CAS 北大核心 2024年第14期132-144,共13页 Feed Industry
基金 山东省科技成果转移转化补助(鲁渝科技协作)项目:加州鲈工厂化循环水养殖精准智能测控技术应用及示范[课题编号:2022LYXZ012]。
关键词 水产养殖 智能投饵 机器视觉 声学 水质参数 生物模型 aquaculture intelligent feeding machine vision acoustics water quality parameter biologi-cal model
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