全球智慧农业领域研究态势分析

doi:10.13998/j.cnki.issn1002-1248.20-1180

摘要/Abstract

摘要： [目的/意义]通过对全球智慧农业领域的研究态势进行分析,以期为当下及今后中国智慧农业领域的科技创新与管理决策提供数据参考和情报支撑。[方法/过程]基于Web of Science数据库,利用文献计量和知识图谱等方法,针对全球范围内智慧农业的研究概况、研究群体的竞争力、研究重点与热点等进行深入分析及可视化展示。[结果/结论]2010年之后全球及中国智慧农业的研究热度越来越高;中国和美国的生产力和影响力均遥遥领先于世界其他各国,中国农业大学、浙江大学、美国农业部的生产力和影响力具有明显优势,HE Y、JAYAS D S、BLASCO J的生产力和影响力均较高,中国机构和学者的论文质量普遍不高;农学、计算机科学、工程学、食品科学技术、化学是重点学科领域,Computers and Electronics in Agriculture的期刊竞争力最强;全球及中国智慧农业领域均可分为三大研究主题,但研究重点有所差异;以农业物联网为代表的信息感知、分析与调控技术是近年来的研究热点;农用传感器的自主研发、数据挖掘分析和共享利用的技术模式、智能控制的算法模型和系统集成、智能化农机装备和农业机器人自主研发、智慧化农业科技服务模式等是中国智慧农业进一步发展需要突破的重点研究方向。

关键词: 智慧农业, 文献计量, 知识图谱, 竞争力, 研究重点

Abstract: [Purpose/Significance] By analyzing the research situation of global smart agriculture, this paper aims to provide data reference and information support for scientific and technological innovation and management decision-making in the field of smart agriculture in China. [Method/Process] Based on the Web of Science database, this paper makes an in-depth analysis and visualization display of the global smart agriculture research overview, research group competitiveness, research focus and hot spots by using the methods of bibliometrics and knowledge mapping. [Results/Conclusions] Smart agriculture has drawn increasing interest among researchers both in and outside of China since 2010. The productivity and influence of China and the United States are far ahead of those of other countries in the world. The productivity and influence of China Agricultural University, Zhejiang University and the United States Department of Agriculture have obvious advantages. HE Y, JAYAS D S, and BLASCO J have higher productivity and influence, but the quality of papers of Chinese institutions and scholars is generally not rated as high. Agronomy, computer science, engineering, food science and technology, and chemistry are the key disciplines. Computers and Electronics in Agriculture is the most competitive journal. The global and China's smart agriculture can be divided into three research topics, but the research focus is different; the agricultural Internet of things as a representative of information perception, analysis and control technology is a research hotspot in recent years; agricultural sensor independent research and development, data mining analysis and sharing technology model, smart control algorithm model and system integration, smart agricultural machinery equipment and agriculture autonomous research and development of robots and smart agricultural science and technology service mode are the key research directions for further development of smart agriculture in China.

Key words: smart agriculture, bibliometrics, knowledge map, competitiveness, research focus

中图分类号:

G350

任妮, 郭婷, 孙艺伟, 戴红君, 张琤琤. 全球智慧农业领域研究态势分析[J]. 农业图书情报学报, 2021, 33(9): 48-63.

REN Ni, GUO Ting, SUN Yiwei, DAI Hongjun, ZHANG Chengcheng. An Analysis of Global Smart Agriculture Research Situation[J]. Journal of Library and Information Science in Agriculture, 2021, 33(9): 48-63.

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