期刊文献+

植物表型组学:发展、现状与挑战 被引量:68

Plant phenomics: history,present status and challenges
下载PDF
导出
摘要 随着遥感、机器人技术、计算机视觉和人工智能的发展,植物表型组学研究已经步入了快速成长阶段。本文首先介绍了植物表型组学的发展简史,包括其理论核心、研究方法、在生物研究中的应用以及国际上最新的研究动向。然后,针对各类表型技术载体平台如手持、人载、车载、田间实时监控、大型室内外自动化平台和航空机载等,分析这些技术手段在室内、外植物研究中的应用情况和实际问题。为了对表型研究中产生的巨量图像和传感器数据进行量化分析,把大数据转化为有实际意义的性状信息和生物学知识,本文着重讨论了后期表型数据解析和相应的研发过程。最后,提出表型组学的应用前景与未来展望,以期为中国的表型研究提供指导和建议。 With the development of remote sensing,robotics,computer vision and artificial intelligence,plant phenomics research has been developing rapidly in recent years.Here,we first introduced a concise history of this research domain,including the theoretical foundation,research methods,biological applications,and the latest progress.Then,we introduced some important indoor and outdoor phenotyping approaches such as handheld devices,ground-based manual and automated vehicles,robotic systems,Internet of Things(IoT)based distributed platforms,automatic deep phenotyping systems,and large-scale aerial phenotyping,together with their advantages and disadvantages during the applications.In order to extract meaningful information from big image-and sensor-based datasets generated by the phenotyping process,we also specified key phenotypic analysis methods and related development procedures.Finally,we discussed the future perspective of plant phenomics,with recommendations of how to apply this research field to breeding,cultivation and agricultural practices in China.
作者 周济 Francois Tardieu Tony Pridmore John Doonan Daniel Reynolds Neil Hall Simon Griffiths 程涛 朱艳 王秀娥 姜东 丁艳锋 ZHOU Ji;CHENG Tao;ZHU Yan;WANG Xiu’e;JIANG Dong;DING Yanfeng(Plant Phenomics Research Center,Nanjing Agricultural University,Nanjing 210095,China)
出处 《南京农业大学学报》 CAS CSCD 北大核心 2018年第4期580-588,共9页 Journal of Nanjing Agricultural University
关键词 表型组学 多层次表型 遥感 成像技术 机器人技术 物联网 人工智能 高通量性状分析 phenomics multi-scale phenotyping remote sensing imaging robotics Internet of Things(IoT) artificial intelligence high-throughput traits analyses
  • 相关文献

参考文献1

二级参考文献53

  • 1Aguilar I, Misztal I, Tsuruta S, Wiggans GR, Lawlor TJ (2011) Multiple trait genomic evaluation of conception rate in Holsteins. J. Dairy Sci. 94, 2621-2624. 被引量:1
  • 2Aparicio N, Villegas D, Casadesus J, Araus JL, Royo C (2000) Spectral reflectance indices for assessing durum wheat biomass, green area, and yield under Mediterranean conditions. Agron. J. 92, 83-91. 被引量:1
  • 3Araus JL, Casadesus J, Bort J (2001) Recent tools for the screening of physiological traits determining yield. Chapter 5. In: Reynolds M, Ortiz-Monasterio I, McNab A, eds. Application of Physiology in Wheat Breeding. CIMMYT, Mexico, D.F. pp: 59-77. 被引量:1
  • 4Araus JL, Slafer GA, Reynolds MP, Royo C (2002) Plant breeding and water stress in C3 cereals: What to breed for? Ann. Bet. 89, 925-940. 被引量:1
  • 5Araus JL, Bort J, Steduto P, Villegas D, Royo C. (2003) Breeding cereals for Mediterranean conditions: Ecophysiological clues for biotechnology application. Ann. Appl. Biol. 142, 129-141. 被引量:1
  • 6Araus JL, Slafer GA, Royo C, Serret MD (2008) Breeding for yield potential and stress adaptation in cereals. Grit. Rev. Plant Sci. 27, 1-36. 被引量:1
  • 7Babar MA, van Ginkel M, Klatt AR, Prasad B, Reynolds MP (2006) The potential of using spectral reflectance indices to estimate yield in wheat grown under reduced irrigation. Euphytica 150, 155-172. 被引量:1
  • 8Bernardo R, Yu J (2007) Prospects for genome-wide selection for quantitative traits in maize. Crop Sci. 47, 1082-1090. 被引量:1
  • 9Burgueno J, de los Campos G, Weigel K, Crossa J (2012) Genomic prediction of breeding values when modeling genotype × environment interaction using pedigree and dense molecular markers. Crop Sci. doi; 10.2135/cropsci2011.06.0299.×. 被引量:1
  • 10Cabrera-Bosquet L, Sanchez C, Rosales A, Palacios-Rojas N, Araus JL (2011a) NIRS-assessment of δ18O, nitrogen and ash content for improved yield potential and drought adaptation in maize. J. Agric. Food Chem. 59, 467-474. 被引量:1

共引文献12

同被引文献1012

引证文献68

二级引证文献527

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部