基于文献计量的植物表型组学研究进展分析

doi:10.19788/j.issn.2096-6369.190206

摘要/Abstract

摘要：

【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。

关键词: 文献计量学, 植物表型组学, 共现分析, 遥感技术, 机器学习, 计算机视觉, 数据挖掘, 数据采集

Abstract:

[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.

Key words: bibliometrics, plant phenomics, co-occurrence analysis, remote sensing technology, machine learning, computer vision, data mining, data acquisition

中图分类号:

李晓曼,张扬,徐倩,谢能付. 基于文献计量的植物表型组学研究进展分析[J]. 农业大数据学报, 2019, 1(2): 64-75.

Xiaoman Li,Yang Zhang,Qian Xu,Nengfu Xie. Bibliometrics-Based Analysis of Advances in Plant Phenomics Research[J]. Journal of Agricultural Big Data, 2019, 1(2): 64-75.

图/表 13

图 1

图 2

表1

表2

表3

表4

表5

表6

图 3

图 4

图 5

图 6

图 7

参考文献 23

[1]	周济, Tardieu Francois, Pridmore Tony, 等. 植物表型组学:发展、现状与挑战[J]. 南京农业大学学报, 2018,41(04):580-588.
	ZHOU J, Francois Tardieu, Tony Pridmore , et al. Plant phenomics:history, present status and challenges[J]. Journal of Nanjing Agricultural University, 2018,41(4):580-588.
[2]	玉光惠, 方宣钧 . 表型组学的概念及植物表型组学的发展[J]. 分子植物育种, 2009,7(04):639-645.
	Yu G H, Fang X J . Concept of Phenomics and its Development in Plant Science[J]. Molecular Plant Breeding, 2009,7(04):639-645.
[3]	Houle, David, Diddahally R . Govindaraju, and Stig Omholt."Phenomics: the next challenge." Nature reviews genetics11. 12(2010):855-866.
[4]	Mark T, Peter L . Breeding technologies to increase crop production in a changing world[J]. Science, 2010,327(5967):818-822.
[5]	Ribaut J M, De Vicente M C, Delannay X . Molecular breeding in developing countries: challenges and perspectives[J]. Current Opinion in Plant Biology, 2010,13(2):213-218.
[6]	Fiorani, Fabio, and Ulrich Schurr . "Future scenarios for plant phenotyping." Annual review of plant biology 64 ( 2013):267-291.
[7]	Walter, Achim, Frank Liebisch, and Andreas Hund . "Plant phenotyping: from bean weighing to image analysis." Plant methods 11. 1(2015):14.
[8]	Fahlgren, Noah, Malia A. Gehan, and Ivan Baxter ."Lights, camera, action: high-throughput plant phenotyping is ready for a close-up." Current opinion in plant biology 24 ( 2015):93-99.
[9]	Li, Lei, Qin Zhang, and Danfeng Huang . "A review of imaging techniques for plant phenotyping." Sensors 14. 11(2014):20078-20111.
[10]	Andrade-Sanchez P, Gore M A, Heun J T , et al. Development and evaluation of a field-based high-throughput phenotyping platform[J]. Functional Plant Biology, 2013,41(1):68-79.
[11]	Araus J L, Cairns J E . Field high-throughput phenotyping: the new crop breeding frontier[J]. Trends in Plant Science, 2014,19(1):52-61.
[12]	唐惠燕, 倪峰, 李小涛 , 等. 基于Scopus的植物表型组学研究进展分析[J]. 南京农业大学学报, 2018,41(6):1133-1141.
	Tang H Y, Ni F, Li X T , et al. Analysis of the advance in plant phenomics research based on Scopus tools[J]. Journal of Nanjing agricultural University, 2018,41(6):1133-1141.
[13]	Pritchard, Alan . "Statistical bibliography or bibliometrics." Journal of documentation 25. 4(1969):348-349.
[14]	Broadus, Robert . "Toward a definition of “bibliometrics”." Scientometrics 12.5- 6(1987):373-379.
[15]	丁学东 . 文献计量学基础[M]. 北京大学出版社, 1993.
	Ding X D. The Basis of Bibliometrics[M]. Peking University Press, 1993.
[16]	刘雪立 . 10种国际权威科技期刊影响因子构成特征及其启示[J]. 编辑学报, 2014,3(26).
	LIU X L . Structural characteristics of impact factors of the ten top international journals[J]. ACTA EDITOLOGICA, 2014,3(26).
[17]	王文平, 刘云, 何颖 . 国际科技合作对跨学科研究影响的评价研究——基于文献计量学分析的视角[J]. 科研管理, 2015,3(36):127-137.
	Wang W P, Liu Yun, He Ying , et al. A research on the evaluation of effect of international S&T collaboration on interdisciplinary research based on the analysis in bibliometrics[J]. Science Research Management, 2015,3(36):127-137.
[18]	Davis, Larry S., Steven A. Johns, and J.K. Aggarwal . "Texture analysis using generalized co-occurrence matrices." IEEE Transactions on Pattern Analysis & Machine Intelligence 3 ( 1979):251-259.
[19]	Zucker, Steven W., and Demetri Terzopoulos . "Finding structure in co-occurrence matrices for texture analysis." Computer graphics and image processing 12. 3(1980):286-308.
[20]	牛奉高, 王菲菲, 邱均平 . 中国高等教育评价研究的主题及其演变分析[J]. 重庆大学学报(社会科学版), 2013,19(1):104-110.
	NIU F G, WANG F F, QIU J P . On Themes and Its Evolution of Chinese Tertiary Education Evaluation Study[J]. JOURNAL OF CHONGQING UNIVERSITY(Social Science Edition) , 2013,19(1):104-110.
[21]	胡俊 . 基于本体的共词分析技术在生物医学文献研究热点中的应用研究[D]. 复旦大学, 2011.
	HU J . Application of Ontology-based Co-word Analysis Technology in Research Hotspots of Biomedical Literature.[D]. Fudan University, 2011.
[22]	Milici, Mathias , et al. "Co-occurrence analysis of microbial taxa in the Atlantic Ocean reveals high connectivity in the free-living bacterioplankton." Frontiers in microbiology 7 ( 2016):649.
[23]	Gu, Dongxiao , et al. "Discovering and Visualizing Knowledge Evolution of Chronic Disease Research Driven by Emerging Technologies." IEEE Access ( 2019).

Metrics

Viewed

Full text

296

HTML			PDF

Just accepted	Online first	Issue	Just accepted	Online first	Issue
0	0	17	0	0	279

From	Others	local

Times	63	233
Rate	21%	79%

Abstract

1201

Just accepted	Online first	Issue

0	0	1201

From	Others	local

Times	156	1045
Rate	13%	87%

Cited

Web of Science	Crossref	ScienceDirect	Search for Citations in Google Scholar >>


This page requires you have already subscribed to WoS.

Shared

指标名称	2014年	2015 年	2016 年	2017 年	2018年	合计/平均
核心文献总量	489	598	719	790	797	679
总被引频次	9906	9069	7645	4807	1772	6640
篇均被引频次	20.26	15.17	10.63	6.08	2.22	10.87
H指数	47	45	34	24	13	33
高被引论文	16	16	22	14	17	17
参与国家/地区	64	73	82	79	79	75
参与机构	799	923	1157	1169	1253	1060
参与学者数量	2607	3161	3820	4218	4448	3651

国家	WOS论文数	学科规范化的引文影响力(CNCI值）	被引频次	论文被引百分比	高被引论文	国际合作论文占比％
美国	1789	1. 78	51464	87.20	57	37.28
英国	1196	1.85	34720	89.21	38	49.00
德国	798	1.96	23001	88.72	25	49.75
中国	567	1.36	8062	79.72	12	45.50
法国	546	1.71	14551	89.93	14	53.11
澳大利亚	435	2.05	12510	89.20	18	53.33
西班牙	369	1.62	7607	88.89	12	52.85
意大利	346	1.53	5504	90.75	5	44.51
曰本	332	1.27	7594	84.04	7	32.83
印度	282	0.98	3584	77.66	7	32.62

期刊	WOS 论文数	被引频次	篇均被引频次	期刊规范化引文影响力	期刊影响因子	期刊所在国家
FRONTIERS IN PLANT SCIENCE	216	2452	11. 35	1.24	3.68	SWITZERLAND
PLANT METHODS	136	1883	13.85	1.44	4.27	ENGLAND
PLOS ONE	130	2298	17.68	1.46	2.77	USA
JOURNAL OF EXPERIMENTAL BOTANY	126	4756	37. 75	1.22	5.35	ENGLAND
COMPUTERS AND ELECTRONICS IN AGRICULTURE	122	2811	23.04	1.43	2.43	ENGLAND
PLANT PHYSIOLOGY	118	5865	49.70	1.01	5.95	USA
FUNCTIONAL PLANT BIOLOGY	83	2549	30.71	1.98	2.08	AUSTRALIA
CROP SCIENCE	79	2355	29.81	1.87	1.64	USA
PLANT JOURNAL	67	4024	60.06	1.07	5.77	ENGLAND
THEORETICAL AND APPLIED GENETICS	67	2052	30.63	1.06	3.93	GERMANY (FED REP GER)
ANNALS OF BOTANY	63	1854	29.43	1.34	3.65	ENGLAND
PLANT AND SOIL	63	1799	28.56	1.17	3.31	NETHERLANDS
EUPHYTICA	59	708	12.00	1.23	1.55	NETHERLANDS
REMOTE SENSING	56	1069	19.09	1.9	3.41	SWITZERLAND
NEW PHYTOLOGIST	54	3115	57.69	1.25	7.43	ENGLAND
BMC PLANT BIOLOGY	47	912	19.40	1.15	3.93	ENGLAND
SENSORS	47	929	19.77	2.12	2.47	SWITZERLAND
SCIENTIFIC REPORTS	42	396	9.43	1.16	4.12	ENGLAND
FIELD CROPS RESEARCH	41	1395	34.02	1.34	3.13	NETHERLANDS
PLANT CELL	38	5383	141.66	1.39	8.23	USA