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高通量田间作物表型分析:现状与挑战

High-throughput field crop phenotyping: current status and challenges.

作者信息

Ninomiya Seishi

机构信息

Graduate School of Agriculture and Life Sciences, The University of Tokyo, Nishitokyo, Tokyo 188-0002, Japan.

Plant Phenomics Research Center, Nanjing Agricultural University, Nanjing, China.

出版信息

Breed Sci. 2022 Mar;72(1):3-18. doi: 10.1270/jsbbs.21069. Epub 2022 Feb 17.

DOI:10.1270/jsbbs.21069
PMID:36045897
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8987842/
Abstract

In contrast to the rapid advances made in plant genotyping, plant phenotyping is considered a bottleneck in plant science. This has promoted high-throughput plant phenotyping (HTP) studies, resulting in an exponential increase in phenotyping-related publications. The development of HTP was originally intended for use as indoor HTP technologies for model plant species under controlled environments. However, this subsequently shifted to HTP for use in crops in fields. Although HTP in fields is much more difficult to conduct due to unstable environmental conditions compared to HTP in controlled environments, recent advances in HTP technology have allowed these difficulties to be overcome, allowing for rapid, efficient, non-destructive, non-invasive, quantitative, repeatable, and objective phenotyping. Recent HTP developments have been accelerated by the advances in data analysis, sensors, and robot technologies, including machine learning, image analysis, three dimensional (3D) reconstruction, image sensors, laser sensors, environmental sensors, and drones, along with high-speed computational resources. This article provides an overview of recent HTP technologies, focusing mainly on canopy-based phenotypes of major crops, such as canopy height, canopy coverage, canopy biomass, and canopy stressed appearance, in addition to crop organ detection and counting in the fields. Current topics in field HTP are also presented, followed by a discussion on the low rates of adoption of HTP in practical breeding programs.

摘要

与植物基因分型的快速进展形成对比的是,植物表型分析被认为是植物科学中的一个瓶颈。这推动了高通量植物表型分析(HTP)研究,导致与表型分析相关的出版物呈指数级增长。HTP的发展最初旨在用作在可控环境下对模式植物物种进行室内HTP的技术。然而,随后它转向了用于田间作物的HTP。尽管由于环境条件不稳定,田间HTP比可控环境下的HTP更难进行,但HTP技术的最新进展已经能够克服这些困难,从而实现快速、高效、无损、非侵入性、定量、可重复和客观的表型分析。数据分析、传感器和机器人技术的进步,包括机器学习、图像分析、三维(3D)重建、图像传感器、激光传感器、环境传感器和无人机以及高速计算资源,加速了HTP的最新发展。本文概述了近期的HTP技术,主要关注主要作物基于冠层的表型,如冠层高度、冠层覆盖率、冠层生物量和冠层胁迫外观,以及田间作物器官的检测和计数。还介绍了田间HTP的当前主题,随后讨论了HTP在实际育种计划中的采用率较低的问题。

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