植物表型平台与图像分析技术研究进展与展望
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国家自然科学基金项目(31371963)、江苏省六大人才高峰项目(NY-058)、江苏省青蓝工程项目(苏教201842)、江苏省333工程项目(苏人20186)、福建省林木种苗科技攻关六期项目(20192021)和江苏高校优势学科建设工程项目


Research Progress and Prospect in Plant Phenotyping Platform and Image Analysis Technology
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    摘要:

    近年来,植物基因组得到迅猛发展,但因缺乏足够的表型数据而限制了人类解析数量性状遗传学的能力。通过开发植物表型信息采集平台和进行图像分析可以加以解决。高通量、自动化、高分辨率的植物表型信息采集平台与分析技术对于加快植物改良和育种、提高产量和抗病虫害能力至关重要。将植物表型平台信息采集平台与分析技术用于解析基因组信息,定量研究与生长、产量和适应生物或非生物胁迫相关的复杂性状,是建立植物生长模型和采集农作物高维、丰富表型数据集的重要途径,能够满足填补基因组信息与植物表型可塑性之间空白的需要。阐述了基于光学成像的植物表型信息采集平台与图像分析技术的研究进展,从室内、田间不同的使用环境出发,根据不同搭载方式,总结分析了各表型平台的功能和特点。最后,分析了目前植物表型信息采集平台与分析技术存在的瓶颈问题,提出了以下建议与展望:开发植物表型信息采集平台的多传感器集成系统;将植物生长环境监测模块融入植物表型信息采集平台中;开发针对林木的表型信息采集平台;对传感器获取的表型数据进行更好的集成与挖掘;采用无损原位根系信息采集技术得到植物地下部分的表型数据;构建表型数据统一开放的标准,进行学科交叉的深度合作。

    Abstract:

    In recent years, the rapid development of plant genomes, but the lack of sufficient phenotypic data limits the ability of humans to analyze the genetics of quantitative traits. This problem can be effectively solved by developing a plant phenotypic monitoring platform. High-throughput, automated and high-resolution phenotyping platform is critical for accelerating crop improvement and breeding strategies for higher yield and disease tolerance. Plant phenotyping has been advancing at an accelerated rate as a response to the need to fill the gap between genomic information and the plasticity of the plant phenome. Domestic and international efforts have been made to develop phenotyping facilities, and these devices are actively contributing to the generation of high-dimensional, richly informative datasets about the phenotype of model and crop plants. The plant phenotypic monitoring platform integrates multiple sensors for quantitative research on complex traits related to growth, yield, and adaptation to biotic or abiotic stresses such as plant height, leaf number and area, root morphology, biomass, and fruit characteristics. The research progress of plant phenotypic monitoring technology and research status of platform at home and abroad was mainly introduced. The research progress of plant phenotypic information collection platform and technology was introduced, and the functions and characteristics of each were summarized and analyzed. Thus, various phenotypic platform based on indoor and field environments were presented together with applications of these platforms with different mounting modes. An overview of the most commonly used sensors that empower digital phenotyping and the information they provide were presented. Function and feature of each phenotype platform was also analyzed. Meanwhile, an in-depth analysis of image processing with its major issues was given, and the algorithms that were used or emerged as useful to obtain data out of images in an automatic fashion. In this review, the current and emerging methods of image acquisition and processing that allow image-based phenomics were covered. The main bottlenecks that still remained in the field was concluded and the application prospect of plant phenotypic monitoring technology and platform were expected, which pointed out the following challenges: developing plant phenotyping platform of multi-sensor integrated system, introducing plant growth environment monitoring module into plant phenotypic information collection platform, designing forest phenotypic information collection platform, conducting integration and mining phenotype data captured by sensors, collecting the phenotypic data of underground part by nondestructive in situ plant root measurement technology, building unified open standards for phenotypic data and prompting interdisciplinary cooperation.

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张慧春,周宏平,郑加强,葛玉峰,李杨先.植物表型平台与图像分析技术研究进展与展望[J].农业机械学报,2020,51(3):1-17. ZHANG Huichun, ZHOU Hongping, ZHENG Jiaqiang, GE Yufeng, LI Yangxian. Research Progress and Prospect in Plant Phenotyping Platform and Image Analysis Technology[J]. Transactions of the Chinese Society for Agricultural Machinery,2020,51(3):1-17.

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  • 收稿日期:2019-09-23
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  • 在线发布日期: 2020-03-10
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