【目的】为了掌握植物表型组学研究的发展脉络和现状,本文基于文献计量学方法探讨了植物表型组学的研究现状。【方法】本研究基于Web of Science核心合集数据库分析了1995-2018年的学术论文,利用多个指标从学术产出（年度变化趋势分析、国家和地区分析、期刊分析和学科领域分析）和学术合作（国家合作情况分析和机构合作情况分析）两个方面对植物表型组学文献进行了统计分析。同时,本文使用Web of Science数据库文献分析平台和EXCEL、DDA等软件,利用共词分析方法构建文献关键词共现矩阵,进一步对矩阵进行聚类分析,并利用VOSviewer文献计量工具进行可视化。此外,本文构建了1995-2002年、2003-2010年、2011-2018年三个时间片的关键词共现矩阵,分析了不同时间片主题的变化情况。【结果】本文基于Web of Science共检索到与植物表型组学研究和应用相关的文献6800篇,发现植物表型组学文献数量整体呈上升趋势,现阶段正处于高速增长阶段。从学术产出归属国家和地区分布来看,美国发文量最多,中国排名第四。从国际合作来看,澳大利亚、法国和西班牙国际合作论文占比较高,美国的占比靠后。虽然植物表型组组学研究已经呈现多学科合作发展趋势,但植物科学还是主体领域。从研究主题上看,主要包括遥感技术在表型组学中的应用、植物表型组学基础研究、利用光学成像的图像分析、机器学习和计算机视觉技术、利用不同植物种类如小麦和水稻的相关研究。

[Objective] To understand the development and current state of plant phenomics research, we performed a bibliometrics-based analysis. [Methods] We reviewed entries in the plant phenomics research domain in the Web of Science core collection database from 1995 to 2018 using multiple indicators, such as academic output (e.g. annual trends, countries, journals, and subject areas) and academic collaborations (i.e. national and institutional cooperation). We used the Web of Science database document analysis platform, Excel, DDA software, and a word co-occurrence analysis method and visualized the results with the VOSviewer bibliometric tool. We analyzed changes in research topics during three time periods: 1995 to 2002, 2003 to 2010, and 2011 to 2018. [Results] Based on Web of Science, a total of 6,800 plant phenomics articles, both basic research and applications, have been published. The number of plant phenomics publications is increasing, with an accelerating trend in recent years. In terms of academic output by country, the United States is clearly in the lead, whereas China presently ranks fourth in the world. Papers published by Canadian, Spanish and Italian authors include the largest number of international partnerships, while articles from the United States comprise 37.28% of international collaborations. Although multidisciplinary studies are increasing in the plant phenomics field, plant science is still the main focus of this research domain. Research topics include the application of remote sensing technologies, theoretical issues, time-series imaging analysis techniques, machine learning, computer vision, and research using plant species such as wheat and rice.