作 者：
岳冬冬;王鲁民;方海;曹坤;阮雯;纪炜炜
单 位：
中国水产科学研究院东海水产研究所农业部远洋与极地渔业创新重点实验室;中国水产科学研究院东海水产研究所农业部远洋与极地渔业创新重点实验室农业部东海渔业资源开发利用重点实验室;中国水产科学研究院
关键词：
深水网箱;专利情报分析;智能水产养殖业;对策建议
摘 要：
深水网箱养殖业在中国发展较快,已成为绿色渔业发展的重要路径之一。以单位水体体积产量为指标,可将2007—2017年中国深水网箱养殖业大致分为3个阶段:2007—2011年,2009年单产峰值达13.11 kg/m~3;2011—2015年,2013年单产峰值达到17.79 kg/m~3;2015—2017年,单产基本保持在11 kg/m~3以上。专利情报分析发现,科研院所是深水网箱专利申请主体,投饲系统、收捕系统、水质监控、网衣清洗等智能化控制系统成为技术创新的重要方向。目前深水网箱养殖的主要差距是:信息感知与识别度不高、数据处理与分析能力有待提高、科学决策的路途较长。根据对半潜式大型智能渔业养殖平台的分析,提出深化提升智能深水网箱养殖核心技术、建立智能深水网箱养殖渔业数据分析中心、构建智能深水网箱养殖渔业标准体系和深水网箱养殖渔业信息安全体系等建议,为推动深水网箱养殖业率先实现现代化提供参考。
译 名：
Analysis and Countermeasures of Patent Information on Deep-water Net Cage Aquaculture Science and Technology in China
作 者：
YUE Dong-dong;WANG Lu-min;FANG Hai;CAO Kun;RUAN Wen;JI Wei-wei;Key Laboratory of Oceanic and Polar Fisheries, Ministry of Agriculture,Key Laboratory of East China Sea Fishery Resources Exploitation, Ministry of Agriculture,East China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences;Chinese Academy of Fishery Sciences;
单 位：
YUE Dong-dong%WANG Lu-min%FANG Hai%CAO Kun%RUAN Wen%JI Wei-wei%Key Laboratory of Oceanic and Polar Fisheries, Ministry of Agriculture,Key Laboratory of East China Sea Fishery Resources Exploitation, Ministry of Agriculture,East China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences%Chinese Academy of Fishery Sciences
关键词：
deep-water net cage;;patent information analysis;;intelligent aquaculture;;countermeasures
摘 要：
Deep-water net cage aquaculture has been rapidly developed and become an important path for development of green fisheries in China. The deep-water net cage aquaculture industry in China from 2007 to 2017 can be broadly divided into three stages using unit volumetric volume production as an indicator: from 2007 to 2011, with the peak output of 13.11 kg/m~3 in 2009; from 2011 to 2015, with the peak yield of 17.79 kg/m~3 in 2013; and from 2015 to 2017, with the constant yield of more than 11 kg/m~3. The patent information analysis revealed that the most patents for deep-water net cages culture were derived from scientific research institutes, and intelligent control systems including feeding systems, collection systems, water quality monitoring, and net washing were the important directions for technological innovation. The gaps in science and technology for deep-water net cage aquaculture between China and foreign countries are mainly manifested in the low level of information perception and recognition, further improving the data processing and analysis capabilities, and the long distance for scientific decision-making. On the basis of a case study of a semi-submersible large-scale intelligent aquaculture platform, we propose to deepen the core technologies of intelligent deep-water net cage aquaculture, to establish an intelligent deep-water net cage aquaculture data analysis center, and to build an intelligent deep-water net cage aquaculture standard system, and information security system and to other proposals in order to promote the leading deep-water net cage aquaculture industry in modernization.
