农业大数据学报 ›› 2021, Vol. 3 ›› Issue (1): 56-65.doi: 10.19788/j.issn.2096-6369.210106

• 专题——农产品单品种大数据 • 上一篇    下一篇

大闸蟹养殖大数据分析模型和应用进展

段青玲1,2,3(), 刘怡然1,2,3, 周新辉1,2,3, 任妮4, 李道亮1,2,3()   

  1. 1.中国农业大学国家数字渔业创新中心,北京 100083
    2.中国农业大学信息与电气工程学院,北京 100083
    3.北京市农业物联网工程技术研究中心,北京 100083
    4.江苏省农业科学院农业信息研究所,南京 210014
  • 收稿日期:2021-02-18 出版日期:2021-03-26 发布日期:2021-05-18
  • 通讯作者: 李道亮 E-mail:dqling@ cau.edu.cn;dliangl@ cau.edu.cn
  • 作者简介:段青玲,女,博士,教授,研究方向: 主要从事智能信息处理和农业大数据研究;E-mail: dqling@ cau.edu.cn
  • 基金资助:
    江苏省农业科技自主创新资金项目(CX(19)1003);宁波市公益类科技计划项目(202002N3034)

Progress in Analysis Models and the Application of Big Data in Chinese Mitten Crab Culturing

Qingling Duan1,2,3(), Yiran Liu1,2,3, Xinhui Zhou1,2,3, Ni Ren4, Daoliang Li1,2,3()   

  1. 1.China National Innovation Center of Digital Fishery, Beijing 100083, China
    2.College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China
    3.Beijing Engineering and Technology Research Center for the Internet of Things in Agriculture, Beijing 100083, China
    4.Institute of Agricultural Information, Jiangsu Academy of Agricultural Sciences, Nanjing 210014, China
  • Received:2021-02-18 Online:2021-03-26 Published:2021-05-18
  • Contact: Daoliang Li E-mail:dqling@ cau.edu.cn;dliangl@ cau.edu.cn

摘要:

大闸蟹是我国特有的名优水产养殖品种,随着大闸蟹单品种大数据建设的推进,利用大数据分析技术挖掘数据潜在价值,成为促进大闸蟹产业链升级的重要手段。大数据分析模型是应用大数据技术理清数据相互关系,发掘事物内在规律的重要工具,对大数据技术能否在大闸蟹养殖领域成功应用,促进大闸蟹养殖产业升级有决定性影响。本文重点梳理了大闸蟹养殖大数据分析模型在水质预测预警、水质调控、投喂策略、病害防治、行为分析和品质鉴别等方面的应用进展,介绍了当前大闸蟹养殖大数据的平台建设现状,分析和讨论了大闸蟹养殖大数据分析模型当前面临的问题和发展方向。综述结果表明,大数据技术与大闸蟹全产业链深度融合有其基础和优势,但在利用大数据分析模型解决实际问题时,仍然面临针对性差、应用面窄和关联性低的问题。应充分考虑产业特点,深度挖掘现实需求,从提供智能化数据分析服务并建设多功能的大数据平台方面深化大数据技术在大闸蟹全产业链的应用,以期形成可借鉴、可移植的建设模式,为其他农产品大数据的建设提供参考。

关键词: 大闸蟹养殖, 单品种大数据, 数据分析, 数据模型, 水产大数据, 智慧水产养殖, 农业大数据, 智慧农业

Abstract:

The Chinese mitten crab is a well-known aquaculture product in China. With the development of a big data platform supporting the Chinese mitten crab industry chain, big data technologies can be used to generate insights and value from the data produced during crab culturing, becoming an important way to promote the upgrade of the hairy crab industry chain. Analysis models using big data can clarify the relationships among vast amounts of data and reveal the internal laws of crab farming. A study of these models examines whether big data technologies can be applied to crab culturing to successfully upgrade the crab industry. This paper summarizes the status and performance of several big data models focused on important problems in crab farming. These problems include water quality prediction and early warning, water quality control, feeding strategy, disease detection, behavior recognition, and product quality identification. Several big data platforms currently used in the crab industry are reviewed and the challenges and opportunities of big data analytic models in crab farming are discussed. The review highlights the foundations and advantages in thoroughly applying big data technologies in the crab farming industry, but also highlights challenges in solving practical problems, and the lack of targeted and associated research findings. To reinforce the application of big data technologies, the special characteristics and practical requirements of the industry should be considered when building analysis models, and more intelligent services should be provided on a big data platform for the crab industry. The construction of an effective big data platform on crabs can guide the construction of big data platforms for other agricultural products.

Key words: chinese mitten crab, big data of specific product, data analysis, data model, aquatic big data, smart aquaculture, agricultural big data, smart agriculture

中图分类号: 

  • TP311.1