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(4): 580-588.

ZHOU Ji, Tardieu Francois, Pridmore Tony, et al. Plant phenomics:history, present status and challenges[J]. Journal of Nanjing Agricultural University, 2018, 41(4): 580-588.  DOI: 10.7685/jnau.201805100

植物表型组学:发展、现状与挑战

周济1,2,3

, Tardieu Francois4 , Pridmore Tony5 , Doonan John6 , Reynolds Daniel2 , Hall Neil2 , Griffiths Simon7 , 程涛1 , 朱艳1 , 王秀娥1 , 姜东1 , 丁艳锋1     

1. 南京农业大学植物表型组学研究中心, 江苏 南京 210095;
2. Earlham Institute, Norwich Research Park, Norwich, NR4 7UZ, UK;
3. University of East Anglia, Norwich Research Park, Norwich, NR4 7TJ, UK;
4. INRA, University of Montpellier, LEPSE, 2 Place Viala, E34060 Montpellier, France;
5. University of Nottingham, Nottingham, NG7 2RD, UK;
6. Aberystwyth University, IBERS, Aberystwyth, SY23 3DA, UK;
7. John Innes Centre, Norwich Research Park, Norwich, NR4 7UH, UK

收稿日期：2018-05-31

作者简介：周济, 教授, 研究方向为表型组学、系统开发、机器学习、图像分析、小麦育种, E-mail:ji.zhou@njau.edu.cn, ji.zhou@earlham.ac.uk

通信作者：周济.

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。

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   

Plant phenomics:history, present status and challenges

ZHOU Ji1,2,3

, Tardieu Francois4, Pridmore Tony5, Doonan John6, Reynolds Daniel2, Hall Neil2, Griffiths Simon7, CHENG Tao1, ZHU Yan1, WANG Xiu'e1, JIANG Dong1, DING Yanfeng1    

1. Plant Phenomics Research Center, Nanjing Agricultural University, Nanjing 210095, China;
2. Earlham Institute, Norwich Research Park, Norwich, NR4 7UZ, UK;
3. University of East Anglia, Norwich Research Park, Norwich, NR4 7TJ, UK;
4. INRA University of Montpellier, LEPSE, 2 Place Viala, E 34060 Montpellier, France;
5. University of Nottingham, Nottingham, NG7 2RD, UK;
6. Aberystwyth University, IBERS, Aberystwyth, SY23 3DA, UK;
7. John Innes Centre, Norwich Research Park, Norwich, NR4 7UH, UK

Abstract: 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.

表型组学 多层次表型 遥感 成像技术 机器人技术

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