基于Web of Science世界杨梅研究态势分析

doi:10.11924/j.issn.1000-6850.casb16010133

中国农学通报 ›› 2016, Vol. 32 ›› Issue (16): 178-184.doi: 10.11924/j.issn.1000-6850.casb16010133

基于Web of Science世界杨梅研究态势分析

李梦莎,王化,周丽萍,朱良玉,张悦

(黑龙江省科学院自然与生态研究所,哈尔滨 150040）

收稿日期:2016-01-27 修回日期:2016-03-18 接受日期:2016-04-20 出版日期:2016-06-17 发布日期:2016-06-17
通讯作者: 李梦莎
基金资助:
黑龙江省科学院青年创新基金重点资助项目“黑果腺肋花楸花色苷分离纯化及抗癌活性初步研究”(ZRS201501)。

Research Tendency of Myrica rubra Sieb.et Zucc Based on Web of Sciences

Li Mengsha, Wang Hua, Zhou Liping, Zhu Liangyu, Zhang Yue

(Institute of Nature and Ecology, Heilongjiang Academy of Sciences, Harbin 150040)

Received:2016-01-27 Revised:2016-03-18 Accepted:2016-04-20 Online:2016-06-17 Published:2016-06-17

摘要/Abstract

摘要： 基于Web of Science数据库，采用文献计量学方法，分别对世界上研究最前沿的20个研究机构、研究作者、学术期刊、学科和国家进行了文献计量学统计，进而了解2004—2014年杨梅研究概况和动态。结果表明：2004—2014年世界杨梅研究论文数量共163篇；文献产出量逐年增加，2013年文献数量最高；中国、日本、美国、澳大利亚、新西兰文献数量居世界前5位，中国文献数量最多，为108篇；浙江大学、浙江农业科学院、中国科学院、广东药学院、京都大学杨梅文献较多；最有学术影响力的核心作者来自中国，主要核心期刊是Food Chemistry、Journal of Agricultural and Food Chemistry、Journal of Natural Products、Scientia Horticulturae、BMC Genomics；主要学科是食品科学技术、植物科学、应用化学、化学药物、药理学。

关键词: 蔬菜价格, 蔬菜价格, 周期波动, 季节调整, 预测

Abstract: Literatures on Myrica rubra from 2004 to 2014 based on the Web of Science database were analyzed. The general trend, top 20 countries, research institutes, core authors, key journals and major research disciplines were retrieved. The results indicated that a total of 163 literatures on Myrica rubra were identified. The literature number increased year by year in the world, and the number of 2013 was the highest. The top 5 prolific countries were China, Japan, the United States, Australia and New Zealand. Chinese literatures on Myrica rubra were up to 108, which was higher than that of other countries. The top prolific institutes with high academic achievements were Zhejiang University, Zhejiang Academy of Agricultural Sciences, Chinese Academy of Sciences, Guangdong Pharmaceutical University and Kyoto University. The core authors with high academic achievements were mainly from China. Food Chemistry, Journal of Agricultural and Food Chemistry, Journal of Natural Products, Scientia Horticulturae, BMC Genomics were the most active journals in this field. The main disciplines of Myrica rubra research were food science technology, plant science, chemistry applied, chemistry medicinal and pharmacology pharmacy.

中图分类号:

Q948

李梦莎,王化,周丽萍,朱良玉,张悦. 基于Web of Science世界杨梅研究态势分析[J]. 中国农学通报, 2016, 32(16): 178-184.

Li Mengsha,Wang Hua,Zhou Liping,Zhu Liangyu and Zhang Yue. Research Tendency of Myrica rubra Sieb.et Zucc Based on Web of Sciences[J]. Chinese Agricultural Science Bulletin, 2016, 32(16): 178-184.

参考文献

[1] 潘鸿.广西野生杨梅资源调查及遗传多样性研究[D].南宁:广西大学,2008.
[2] 张宇环.杨梅汁中酚类物质及抗氧化性的研究[D].杭州:浙江大学,2008.
[3] 孙石磊.杨梅抑菌成分及其分离分析[D].无锡:江南大学,2008.
[4] 徐国能.杨梅品种果汁加工特性研究[D].杭州:浙江大学,2007.
[5] 孙秀焕,路文如.基于Web of Science的水稻研究态势分析[J].中国水稻科学,2012,26(5):607-614.
[6] Meho L I, Yang K. Impact of data sources on citation counts and rankings of LIS faculty: Web of Science versus Scopus and Google Scholar[J]. Journal of the American society for information science and technology, 2007,58(13):2105-2125.
[7] 杨华,王小萍,干文芝,等.基于Web of Science的国际茶多酚类研究文献发展态势分析[J].茶叶科学,2013(6):541-549.
[8] 张文宇,张伟欣,葛道阔,等.基于Web of Science近10年油菜研究态势分析[J].中国农业科技导报,2014,6:164-172.
[9] 毛萍,黄东晓,王芋华,等.基于Web of Science的浮萍研究态势分析[J].中国农业科技导报,2014,3:177-184.
[10] 张庆田,范书田,王振兴,等.基于Web of Science的五味子研究态势分析[J].北方园艺,2015,10:184-186.
[11] 刘婧.文献作者分布规律研究——对近十五年来国内洛特卡定律,普赖斯定律研究成果综述[J].情报科学,2004,22(1):123-128.
[12] Zhang X, Huang H, Zhang Q, et al. Phytochemical Characterization of Chinese Bayberry (Myrica rubra Sieb. et Zucc.) of 17 Cultivars and Their Antioxidant Properties[J]. International Journal of Molecular Sciences,2015,16(6):12467-12481.
[13] Liu X F, Yin X R, Allan A C, et al. The role of and in regulating anthocyanin biosynthetic genes in tobacco and Chinese bayberry during anthocyanin biosynthesis[J]. Plant Cell Tissue & Organ Culture,2013,115:285-298.
[14] Zhang S Y, Feng C, Xu C J, et al. Polymorphisms in different EST-SSR types derived from the Chinese bayberry Myrica rubra, Myricaceae) transcriptome[J]. Genetics & Molecular Research Gmr,2015,14:6037-6041.
[15] Tao W, Lu S, Xia Q, et al. Separation and purification of amygdalin from thinned bayberry kernels by macroporous adsorption resins[J]. J Chromatogr B Analyt Technol Biomed Life Sci,2015,975:52-58.
[16] Yi X X, Min Z, Zhong X F, et al. How to improve bayberry (Myrica rubra Sieb. et Zucc.) juice flavour quality: Effect of juice processing and storage on volatile compounds[J]. Food Chemistry,2014,151(4):40-46.
[17] Zhang S M, Gao Z S, Xu C J, et al. Genetic diversity of Chinese bayberry (Myrica rubra Sieb. et Zucc.) accessions revealed by amplified fragment length polymorphism[J]. Hortscience,2009,44(2):487-491.
[18] Feng C, Chen M, Xu C J, et al. Transcriptomic analysis of Chinese bayberry (Myrica rubra) fruit development and ripening using RNA-Seq[J]. BMC Genomics,2012,13(2):1-15.
[19] Sun C, Huang H, Xu C, et al. Biological Activities of Extracts from Chinese Bayberry (Myrica rubra Sieb. et Zucc.): A Review[J]. Plant Foods for Human Nutrition,2013,68(2):97-106.
[20] Fang Z, Zhang M, Wang L. HPLC-DAD-ESIMS analysis of phenolic compounds in bayberries (Myrica rubra Sieb. et Zucc.)[J]. Food Chemistry,2007,100(2):845-852.
[21] Fang Z, Zhang M, Sun Y, et al. Polyphenol oxidase from bayberry (Myrica rubra Sieb. et Zucc.) and its role in anthocyanin degradation[J]. Food Chemistry,2007,103(2):268-273.
[22] 何新华,陈力耕,陈怡,等.中国杨梅资源及利用研究评述[J].果树学报,2004,21(5):467-471.
[22] Bao J, Cai Y, Sun M, et al. Anthocyanins, flavonols, and free radical scavenging activity of Chinese bayberry (Myrica rubra) extracts and their color properties and stability[J]. Journal of Agricultural and Food Chemistry,2005,53(6):2327-2332.
[23] Feng C, Chen M, Xu C J, et al. Transcriptomic analysis of Chinese bayberry (Myrica rubra) fruit development and ripening using RNA-Seq[J]. Bmc Genomics,2012,13(2):1-15.
[24] Niu S, Xu C, Zhang W, et al. Coordinated regulation of anthocyanin biosynthesis in Chinese bayberry (Myrica rubra) fruit by a R2R3 MYB transcription factor. Planta[J]. Planta, 2010, 231(4):887-99.
[25] Fang Z, Zhang Y, Yuan L, et al. Phenolic compounds and antioxidant capacities of bayberry juices[J]. Food Chemistry,2009,113(4):884-888.
[26] Fang Z, Zhang M, Wang L. HPLC-DAD-ESIMS analysis of phenolic compounds in bayberries (Myrica rubra Sieb. et Zucc. )[J]. Food Chemistry,2007,100(2):845-852.
[27] Xuepin L, Zhongbi L, Xiao D, et al. Collagen fiber immobilized Myrica rubra tannin and its adsorption to UO₂(²⁺)[J]. Environmental Science & Technology,2004,38(1):324-328.
[29] Yoshikawa M, Matsuda H T, Xie H, et al. Phenylethanoid oligoglycosides and acylated oligosugars with vasorelaxant activity from Cistanche tubulosa[J]. Bioorganic & Medicinal Chemistry,2006,14(22):7468-7475.

基于Web of Science世界杨梅研究态势分析

Research Tendency of Myrica rubra Sieb.et Zucc Based on Web of Sciences

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics

本文评价

关于本刊

作者中心

审者中心

在线期刊

联系我们

[1]	刘现, 杨航, 李健翔, 俞鉴签. 基于图像的金桔重量预测方法研究[J]. 中国农学通报, 2022, 38(34): 138-143.
[2]	陈嘉聪, 黄永德, 朱文娟, 叶文芳, 翁嘉, 黄秀丽, 陈榕德, 陈水叨. 基于Arrhenius方程建立湿米粉货架期预测模型的研究[J]. 中国农学通报, 2022, 38(33): 132-138.
[3]	赵桂琼, 邓锐捷, 陈志龙, 蔡欣明, 陈乐. 成都市秋桂开花期气象指标及预测[J]. 中国农学通报, 2022, 38(29): 135-139.
[4]	朱晓翠, 郑健, 陈妙金, 沈艳, 李军, 岳俗甲, 杨怡曼. 基于小时气温资料的桃树需冷量和需热量研究[J]. 中国农学通报, 2022, 38(11): 84-88.
[5]	景辉, 杨华, 赵惠瑾, 孟瑶. 基于幼果期气象数据苹果产量早期预测研究——以运城市为例[J]. 中国农学通报, 2021, 37(8): 132-136.
[6]	杨国航, 李琼, 和利钊, 顾静, 牛婧, 张海欧, 郑子健, 赵振. 晚稻全生育期Cd的迁移转化规律及预测模型研究[J]. 中国农学通报, 2021, 37(25): 1-10.
[7]	王祥会, 焦玉霞, 王圣楠, 惠祥海, 闫硕. 鲁西南地区灯诱昆虫种类调查及优势种群动态分析[J]. 中国农学通报, 2021, 37(2): 116-122.
[8]	程智超, 吴文彦, 宋永辉, 隋心, 李梦莎, 杨立宾. 城市生活垃圾堆放对土壤细菌群落结构和功能的影响[J]. 中国农学通报, 2021, 37(17): 72-79.
[9]	王美玉, 戴长雷, 张凯文, 韩心宇. 区域水土保持水土流失预测分析及实例研究[J]. 中国农学通报, 2021, 37(14): 72-77.
[10]	代磊, 王志杰, 张万胜. 贵阳市1998—2018年土地资源承载力分析与预测[J]. 中国农学通报, 2021, 37(1): 108-115.
[11]	符云聪, 朱晓龙, 袁毳, 解晓露, 李鹏祥, 朱维, 黎红亮, 刘代欢. 小麦对镉的吸收、富集及其镉污染预测研究进展[J]. 中国农学通报, 2020, 36(6): 37-41.
[12]	王秋京, 马国忠, 王萍, 赵克葳, 杨晓强, 于瑛楠, 王铭, 姜丽霞. 黑龙江省三种水稻热量指数预测方法的对比研究[J]. 中国农学通报, 2020, 36(5): 1-7.
[13]	田艺心, 高凤菊, 曹鹏鹏, 高琪, 李宏波. 正交多项式回归在高蛋白大豆施肥及经济效益中的预测模型应用[J]. 中国农学通报, 2020, 36(33): 31-37.
[14]	张宝文, 王川, 杨春英, 王来刚. 基于时间序列SVR模型的玉米价格预测研究[J]. 中国农学通报, 2020, 36(31): 115-120.
[15]	孔令博, 王晶静, 林巧, 何微, 杨小薇. 全球玉米分子育种专利态势分析[J]. 中国农学通报, 2020, 36(31): 121-129.