基于Web of science 文献计量分析的蒂腐病研究进展

Bibliometric analysis of stem end rot based on the literature from Web of Science

摘要

为了解目前蒂腐病研究热点和趋势，利用文献计量学方法，通过 CiteSpace 软件分析 2009-2024 年间 Web of Science 核心数据库中收录的 367 篇蒂腐病相关文献，研究蒂腐病领域的力量分布、知识基础、研究热点及前沿趋势等。结果表明，蒂腐病研究文献数量呈上升趋势，中国、美国和巴西发文量较多，国家之间的合作也较多。美国农业部是该领域顶尖的研究机构，中国领先机构为海南大学。研究机构间合作紧密，但中国机构在国际合作和学术影响力方面有待提升。蒂腐病研究领域发文量较高作者有 Alkan Noam、Bai Jinhe 等。通过关键词共现及突发性检测分析发现，目前蒂腐病研究热点包括病原菌鉴定、抗性及基因组研究。未来研究应加强跨学科合作，深入探讨蒂腐病的病理机制及防治策略，为作物健康生长提供保障。

Abstract

In order to understand the current research hotspots and trends of stem end rot disease, a bibliometric analysis was conducted using CiteSpace software on 367 stem end rot disease-related articles indexed in the Web of Science core database between 2009 and 2024. The distribution of research efforts, knowledge base, research hotspots, and frontier trends in the field of stem end rot disease were analyzed. The results indicate that the number of publications on stem end rot disease has been increasing, with China, the United States, and Brazil having the highest publication volumes. There is also significant international collaboration among countries. The United States Department of Agriculture (USDA) is a leading research institution in this field, while Hainan University is the leading institution in China. Research institutions collaborate closely, although Chinese institutions still have room to improve in terms of international cooperation and academic influence. Prominent authors in the field of stem end rot disease research include Alkan Noam and Bai Jinhe. Keyword co-occurrence and burst detection analysis reveal that current research hotspots in the field include pathogen identification, resistance, and genomics. Future research should focus on strengthening interdisciplinary collaboration, further exploring the pathological mechanisms of stem end rot disease, and developing control strategies to ensure the healthy growth of crops.

关键词

蒂腐病 / 文献计量学 / CiteSpace / 可视化分析

Key words

stem end rot / bibliometrics / CiteSpace / visualization analysis

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基金资助

海南省重点研发计划项目(ZDYF2024XDNY178)