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Unmanned Aerial Vehicle Remote Sensing for Field-Based Crop Phenotyping: Current Status and Perspectives

机译:基于田间作物表型的无人机遥感:现状与展望

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摘要

Phenotyping plays an important role in crop science research; the accurate and rapid acquisition of phenotypic information of plants or cells in different environments is helpful for exploring the inheritance and expression patterns of the genome to determine the association of genomic and phenotypic information to increase the crop yield. Traditional methods for acquiring crop traits, such as plant height, leaf color, leaf area index (LAI), chlorophyll content, biomass and yield, rely on manual sampling, which is time-consuming and laborious. Unmanned aerial vehicle remote sensing platforms (UAV-RSPs) equipped with different sensors have recently become an important approach for fast and non-destructive high throughput phenotyping and have the advantage of flexible and convenient operation, on-demand access to data and high spatial resolution. UAV-RSPs are a powerful tool for studying phenomics and genomics. As the methods and applications for field phenotyping using UAVs to users who willing to derive phenotypic parameters from large fields and tests with the minimum effort on field work and getting highly reliable results are necessary, the current status and perspectives on the topic of UAV-RSPs for field-based phenotyping were reviewed based on the literature survey of crop phenotyping using UAV-RSPs in the Web of Science™ Core Collection database and cases study by NERCITA. The reference for the selection of UAV platforms and remote sensing sensors, the commonly adopted methods and typical applications for analyzing phenotypic traits by UAV-RSPs, and the challenge for crop phenotyping by UAV-RSPs were considered. The review can provide theoretical and technical support to promote the applications of UAV-RSPs for crop phenotyping.
机译:表型分析在作物科学研究中起着重要作用。准确,快速地获取不同环境中植物或细胞表型信息有助于探索基因组的遗传和表达方式,从而确定基因组信息与表型信息之间的联系,从而提高农作物的产量。获取作物特征(例如植物高度,叶色,叶面积指数(LAI),叶绿素含量,生物量和产量)的传统方法依赖于人工采样,这既费时又费力。配备不同传感器的无人机遥感平台(UAV-RSP)近来已成为实现快速和无损高通量表型分析的重要方法,并且具有灵活方便的操作,按需访问数据和高空间分辨率的优势。 UAV-RSP是研究表型和基因组学的强大工具。由于希望使用UAV进行表型分析的方法和应用适合那些希望从大的领域中获得表型参数并希望以最小的工作量进行现场测试并获得高度可靠的结果的用户,因此关于UAV-RSP主题的现状和观点在Web of Science™核心文献数据库中,使用UAV-RSP对作物表型进行了文献调查,并基于NERCITA的案例研究,对基于田间表型的定性进行了综述。考虑了选择无人机平台和遥感传感器的参考,通过UAV-RSP分析表型特征的常用方法和典型应用以及通过UAV-RSP进行作物表型分析的挑战。该综述可以提供理论和技术支持,以促进UAV-RSP在作物表型研究中的应用。

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