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

机译:无人驾驶空中车辆遥感基于现场的作物表型:当前状态和观点

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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:表型在作物科学研究中起着重要作用;对不同环境中植物或细胞的表型信息的准确和快速获取有助于探索基因组的遗传和表达模式,以确定基因组和表型信息的关联,以增加作物产量。用于获取作物特征的传统方法,例如植物高度,叶子颜色,叶面积指数(LAI),叶绿素含量,生物质和产量,依靠手动采样,这是耗时和费力的耗时。无人驾驶飞行器遥感平台(UAV-RSP)配备不同的传感器,最近成为快速和无损高吞吐量表型的重要方法,具有灵活便捷的操作,按需访问数据和高空间分辨率。 UAV-RSP是学习表情和基因组学的强大工具。作为现场表型的方法和应用,对愿意从大型领域的表型参数衍生出来的现场工作的表型参数的用户和应用以及必要的最低努力以及获得高度可靠的结果,是无人机-RSP主题的当前状态和观点对于基于现场的表型,根据科学网站UAV-RSP的作物表型的文献调查审查了吗?核心收集数据库和核案例研究。考虑了用于分析UAV-RSP的常用方法和常见方法的参考,常用的方法和典型的应用,以及通过UAV-RSP对作物表型的挑战。审查可以提供理论和技术支持,以促进UAV-RSP促进作物表型的应用。

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