IBG-2: Plant Sciences, Institute of Bio- and Geosciences, Forschungszentrum Jülich, 52425 Jülich, Germany; email:
Institute for Botany and Molecular Genetics, BioSC, RWTH Aachen University, 52074 Aachen, Germany.
Annu Rev Plant Biol. 2020 Apr 29;71:689-712. doi: 10.1146/annurev-arplant-042916-041124. Epub 2020 Feb 25.
Plant phenotyping enables noninvasive quantification of plant structure and function and interactions with environments. High-capacity phenotyping reaches hitherto inaccessible phenotypic characteristics. Diverse, challenging, and valuable applications of phenotyping have originated among scientists, prebreeders, and breeders as they study the phenotypic diversity of genetic resources and apply increasingly complex traits to crop improvement. Noninvasive technologies are used to analyze experimental and breeding populations. We cover the most recent research in controlled-environment and field phenotyping for seed, shoot, and root traits. Select field phenotyping technologies have become state of the art and show promise for speeding up the breeding process in early generations. We highlight the technologies behind the rapid advances in proximal and remote sensing of plants in fields. We conclude by discussing the new disciplines working with the phenotyping community: data science, to address the challenge of generating FAIR (findable, accessible, interoperable, and reusable) data, and robotics, to apply phenotyping directly on farms.
植物表型分析可实现对植物结构和功能以及与环境相互作用的非侵入式定量分析。高通量表型分析可达至以前无法触及的表型特征。科学家、预培育者和培育者在研究遗传资源的表型多样性并将越来越复杂的性状应用于作物改良时,产生了多样化、具有挑战性和有价值的表型分析应用。非侵入式技术用于分析实验和培育群体。我们涵盖了种子、芽和根性状的受控环境和田间表型分析的最新研究。一些具有代表性的田间表型分析技术已经成为最新技术,并有望加快早期世代的培育进程。我们重点介绍了在田间对植物进行近程和远程感应背后的技术。最后,我们讨论了与表型分析社区合作的新学科:数据科学,以应对生成 FAIR(可发现、可访问、可互操作和可重复使用)数据的挑战,以及机器人技术,直接在农场应用表型分析。