基于文献计量学的智慧农业研究现状及趋势分析
作者:
作者单位:

华中农业大学图书馆,武汉 430070

作者简介:

通讯作者:

周迪,E-mail: zd@mail.hzau.edu.cn

中图分类号:

S126;G250.73

基金项目:

湖北省知识产权局专利信息公共服务基础资源建设项目;华中农业大学图书馆馆内科研项目郑倩,E-mail: qianzheng@mail.hzau.edu.cn


Current status and trend of studying smart agriculture based on bibliometric analysis
Author:
Affiliation:

Library of Huazhong Agricultural University, Wuhan 430070, China

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    摘要:

    智慧农业融合了现代信息技术、农业机械装备和生物技术,是现代农业的发展趋势。我国正处在从传统农业向智慧农业的转型初期,为给我国智慧农业的发展和研究提供参考借鉴,本研究运用文献计量学方法,分析了SCIE数据库收录的全球智慧农业领域的40 812篇相关文献,对智慧农业的核心知识元素、研究主题和前沿热点进行了深入分析。结果显示,2016年后全球智慧农业领域文献量大幅度增长,中国是全球在该领域发展最为迅速的国家。对智慧农业近10年的632篇高被引论文关键词进行共现聚类显示,智慧农业的核心知识元素包括遥感、人工智能、无人机、物联网和大数据;智慧农业可分为三大研究主题:以生物大数据为代表的现代生物技术,以物联网、人工智能和遥感为代表的信息技术,以无人机和农业机器人为代表的智能农机装备。智慧农业的发展是多学科交叉融合实现农业生产高度精确化、智能化、高效化的过程。关键词演化分析显示,以物联网为代表的信息感知、处理和管理以及以机器学习和深度学习为代表的人工智能算法是近年来智慧农业研究的前沿热点。从政策制定、人才培养和核心技术等方面对智慧农业的未来发展进行了讨论,提出通过布局重点领域、培养新型应用型人才和开发原创性成果等方面实现我国农业转型升级。

    Abstract:

    Smart agriculture integrates modern information technology, agricultural machinery and equipment, and biotechnology, which is the development trend of modern agriculture. China is in the early stage of transitioning from traditional agriculture to intelligent agriculture. This article used the bibliometric analysis to analyze 40 812 relevant literatures in the field of global smart agriculture collected by the SCIE database. A knowledge map was drawn to conduct in-depth analysis on the core elements of knowledge, research topics, and cutting-edge hotspots of smart agriculture to provide reference and guidance for the development and study of smart agriculture in China. Results showed that the number of publications in the field of smart agriculture has increased significantly since 2016. China is the country with the fastest development in this field globally. Results of co-occurrence clustering analysis on keywords from 632 highly cited papers on smart agriculture in the past decade showed that the core elements of knowledge in smart agriculture included remote sensing, artificial intelligence, drones, the Internet of Things, and big data. smart agriculture can be divided into three major research topics including modern biotechnology represented by biological big data, information technology represented by the Internet of Things, artificial intelligence and remote sensing, intelligent agricultural machinery and equipment represented by drones and agricultural robots. The development of smart agriculture is a process of interdisciplinary integration to achieve highly precise, intelligent, and efficient agricultural production. Results of analyzing the evolution of keywords showed that information perception, processing, and management represented by the Internet of Things, as well as artificial intelligence algorithms represented by machine learning and deep learning, have been cutting-edge hotspots in smart agriculture research in recent years. The development of smart agriculture in the future was discussed from the perspectives of policy formulation, talent cultivation, and key technologies. It was proposed to achieve the agricultural transformation and upgrading in China by laying out key areas, cultivating new application-oriented talents, and developing original innovation.

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郑倩,李鹏云,周迪.基于文献计量学的智慧农业研究现状及趋势分析[J].华中农业大学学报,2023,42(3):29-38

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  • 收稿日期:2023-03-01
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  • 在线发布日期: 2023-06-20
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