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中国农学通报 ›› 2026, Vol. 42 ›› Issue (10): 179-194.doi: 10.11924/j.issn.1000-6850.casb2025-0607

• 工程·机械·水利·装备 • 上一篇    下一篇

耕整地农机装备研究现状、热点与展望——基于文献计量学

李荣1(), 胡婷婷1, 韦持章2(), 李茜茜1, 闭吉圆1, 孙宇3   

  1. 1 广西壮族自治区科学技术情报研究所, 南宁 530022
    2 广西壮族自治区农业科学院, 南宁 530007
    3 广西大学, 南宁 530004
  • 收稿日期:2025-07-18 修回日期:2026-01-07 出版日期:2026-05-25 发布日期:2026-05-27
  • 通讯作者:
    韦持章,男,1977年出生,广西宾阳人,研究员,硕士,研究方向:果园及茶园农机装备技术。通信地址:530007 广西南宁市大学东路174号,Tel:0771-3242001,E-mail:
  • 作者简介:

    李荣,男,1990年出生,广西平南人,助理研究员,硕士,研究方向:农机装备技术、产业情报研究。通信地址:530022 广西南宁市星湖路24号,Tel:0771-5325507,E-mail:

  • 基金资助:
    广西重点研发计划项目“广西丘陵山区茶园农机装备关键技术研究及应用示范”(桂农科AB241484030); 广西科技发展战略研究专项“广西高端装备产业发展战略研究”(桂科ZL25052003)

Research Status, Hotspots and Prospects of Tillage and Land Preparation Agricultural Machinery and Equipment: A Bibliometric-based Analysis

LI Rong1(), HU Tingting1, WEI Chizhang2(), LI Xixi1, BI Jiyuan1, SUN Yu3   

  1. 1 Institute of Scientific and Technical Information of Guangxi Zhuang Autonomous Region, Nanning 530022
    2 Guangxi Academy of Agricultural Sciences, Nanning 530007
    3 Guangxi University, Nanning 530004
  • Received:2025-07-18 Revised:2026-01-07 Published:2026-05-25 Online:2026-05-27

摘要:

耕整地农机装备是农业生产的重要基础装备,在提升耕作效率、改善土壤质量及推动农业可持续发展方面发挥着关键作用。为揭示国际耕整地农机装备领域的研究态势、合作格局、研究热点及未来发展方向,为该领域学者与行业实践者提供参考,以Web of Science(WoS)核心合集数据库2005—2024年的709篇相关文献为数据源,采用文献计量学方法和科学知识图谱工具进行系统分析。结果发现,国际耕整地农机装备研究发文量近20年来总体保持增长趋势,2011年后进入快速发展阶段,2021年达到峰值77篇。中国在研究产出和学术影响力方面均处于主导地位,形成了以西北农林科技大学、吉林大学等为核心的研究集群,但作者、机构与国家层面的合作网络普遍呈现“内聚”特征,跨国合作仍待加强。研究热点早期主要集中在基础作业效果与关键部件性能优化,中期转向“装备-土壤-作业效果”协同优化,近期引入离散元法(DEM)等数值模拟技术,深入解析土壤-机具互作机理并优化关键部件,并聚焦作业能效、土壤扰动与土壤健康,以及机器视觉、智能仿真等数字化技术的融合应用。当前,国际耕整地农机装备研究正以“性能优化、土壤健康、智能技术”为核心快速发展。未来应重点围绕数字孪生虚实融合设计、具备认知决策能力的智能自主装备,以及与可持续精准农业深度融合的绿色耕作装备技术体系等方向展开深入探索。

关键词: 耕整地农机, CiteSpace, 文献计量学, 知识图谱

Abstract:

Tillage and land preparation machinery are fundamental to agricultural production. They play a crucial role in improving farming efficiency, enhancing soil quality, and promoting sustainable agricultural development. This study aims to reveal the research trends, collaboration landscape, key research topics, and future directions in the field of international tillage and land preparation machinery to provide a valuable reference for scholars and industry practitioners. This study used relevant literature from 2005 to 2024 in the Web of Science (WoS) Core Collection database as the data source, and a total of 709 valid sample papers were obtained after sorting and screening. Using bibliometric methods combined with various scientific knowledge mapping tools, we systematically analyzed the annual publication trends, research entities, collaboration networks, and the evolution of research topics and themes. The number of publications in international tillage and land preparation machinery research showed an overall upward trend over the last two decades. It entered a rapid development phase after 2011, peaking in 2021. China dominated in both research output and academic influence, forming research clusters centered on institutions like Northwest A&F University and Jilin University. However, collaboration networks among authors, institutions, and countries generally showed ‘cohesion’ characteristic, and international cooperation still needed to be strengthened. Initial research hotspots mainly focused on the performance optimization of basic tillage operations and key components. The focus then shifted to the collaborative optimization of ‘implement-soil-tillage performance’. More recently, numerical simulation techniques, such as the discrete element method (DEM), were introduced to deeply analyze the soil-implement interaction mechanism and optimize key components. Current research also focuses on the integration and application of digital technologies like machine vision, intelligent simulation, and the optimization of tillage energy efficiency, soil disturbance, and soil health. International research on tillage and land preparation machinery has entered a rapid development stage centered on ‘performance optimization, soil health, and intelligent technologies’. Future explorations should focus on in-depth research into areas such as digital twin-based virtual-real integration design, intelligent and autonomous equipment with cognitive and decision-making capabilities, and green tillage equipment systems deeply integrated with sustainable and precision agriculture.

Key words: tillage and land preparation machinery, CiteSpace, bibliometrics, knowledge graph

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