摘要
探究农业信息学领域的研究态势、学科结构和研究热点对中国在该领域的高质量发展具有不可或缺的参考意义。梳理了农业信息学的概念起源,以Web of Science核心合集数据库收录的农业信息学领域的相关论文为研究对象,使用可视化分析工具CiteSpace和VOSviewer进行发文趋势、发展脉络、学科结构与研究热点分析。结果表明,农业信息领域的发文量持续增长且近年来增长显著:1995—2005年属于起步阶段、2006—2012年属于缓慢成长阶段、2013—2023年属于快速发展阶段;农业信息学主要的来源学科是工程学、计算机科学、农学、环境生态学和遥感科学,同时也继承了来自地质学、影像科学、植物科学和化学的理论与方法;相关学科分布较为分散,涉及地球科学、农学、植物科学、信息系统、电信等多门学科,表现出较强的跨学科属性;从研究热点的分析可以看出,一是计算机视觉是实现精准农业的关键技术,为智能农机的实时农业图像处理任务提供了高效的解决方案;二是物联网成为智能农业系统的重要基础设施,有效提升自动化生产的效率;三是数字土壤制图与AI技术的结合大力推动土壤的可持续管理。
Exploring the research trend,discipline structure and research hotspots in the field of agricultural informatics is of great reference significance for the high-quality development of this field in China.This study first sorted out the concept origin of agricultural informatics,and then took the relevant papers in the field of agricultural informatics collected in the core collection database of Web of Science as the research object,and used the visual analysis tools Citespace and VOSviewer to analyze the trend of publication,development context,discipline structure and research hotspots.The results show that the number of papers published in the field of agricultural information continues to grow and has increased significantly in recent years:1995—2005 belongs to the initial stage,2006—2012 belongs to the slow growth stage,2013—2023 belongs to the rapid development stage.The main source disciplines of agricultural informatics are engineering,computer science,agronomy,environmental ecology and remote sensing science,and it also inherits theories and methods from geology,imaging science,plant science and chemistry.The distribution of related disciplines is relatively scattered,involving earth science,agronomy,plant science,information system,telecommunications and other disciplines,showing strong interdisciplinary attributes;From the analysis of research hotspots,it can be seen that:First,computer vision is the key technology to realize precision agriculture,which provides an efficient solution for real-time agricultural image processing tasks of intelligent agricultural machines.Second,the Internet of Things has become an important infrastructure for intelligent agricultural systems,effectively improving the efficiency of automated production.Third,the combination of digital soil mapping and AI technology will greatly promote sustainable soil management.
作者
关陟昊
单治易
李甜
赵瑞雪
GUAN Zhi-hao;SHAN Zhi-yi;LI Tian;ZHAO Rui-xue(Institute of Agricultural Information,Chinese Academy of Agricultural Sciences,Beijing 100081,China;Literature and Information Center,Chinese Academy of Sciences,Beijing 100190,China;School of Economics and Management,University of Chinese Academy of Sciences,Beijing 100190;Key Laboratory of Knowledge Mining and Knowledge Service for Agricultural Integrated Publishing,National Press and Publication Administration,Beijing 100081,China)
出处
《湖北农业科学》
2024年第S1期207-213,共7页
Hubei Agricultural Sciences
基金
“农业智能知识服务平台研发与应用示范”项目(2021ZD0113705)
关键词
农业信息学
文献计量
知识图谱
研究热点
agricultural informatics
bibliometrics
knowledge graph
research hotspots
