Guo Wei, Carroll Matthew E, Singh Arti, Swetnam Tyson L, Merchant Nirav, Sarkar Soumik, Singh Asheesh K, Ganapathysubramanian Baskar
Graduate School of Agricultural and Life Sciences, The University of Tokyo, Japan.
Department of Agronomy, Iowa State University, Ames, Iowa, USA.
Plant Phenomics. 2021 Jun 10;2021:9840192. doi: 10.34133/2021/9840192. eCollection 2021.
Unmanned aircraft system (UAS) is a particularly powerful tool for plant phenotyping, due to reasonable cost of procurement and deployment, ease and flexibility for control and operation, ability to reconfigure sensor payloads to diversify sensing, and the ability to seamlessly fit into a larger connected phenotyping network. These advantages have expanded the use of UAS-based plant phenotyping approach in research and breeding applications. This paper reviews the state of the art in the deployment, collection, curation, storage, and analysis of data from UAS-based phenotyping platforms. We discuss pressing technical challenges, identify future trends in UAS-based phenotyping that the plant research community should be aware of, and pinpoint key plant science and agronomic questions that can be resolved with the next generation of UAS-based imaging modalities and associated data analysis pipelines. This review provides a broad account of the state of the art in UAS-based phenotyping to reduce the barrier to entry to plant science practitioners interested in deploying this imaging modality for phenotyping in plant breeding and research areas.
无人机系统(UAS)是植物表型分析的一种特别强大的工具,这得益于其采购和部署成本合理、控制与操作简便灵活、能够重新配置传感器载荷以实现多样化传感,以及能够无缝融入更大的互联表型分析网络。这些优势扩大了基于无人机的植物表型分析方法在研究和育种应用中的使用。本文综述了基于无人机表型分析平台的数据部署、收集、管理、存储和分析的现状。我们讨论了紧迫的技术挑战,确定了植物研究界应了解的基于无人机表型分析的未来趋势,并指出了可以通过下一代基于无人机的成像模式及相关数据分析流程解决的关键植物科学和农艺问题。本综述广泛介绍了基于无人机表型分析的现状,以降低对有兴趣在植物育种和研究领域部署这种成像模式进行表型分析的植物科学从业者的入门门槛。