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用于高通量植物表型分析的机器人技术:当代综述与未来展望

Robotic Technologies for High-Throughput Plant Phenotyping: Contemporary Reviews and Future Perspectives.

作者信息

Atefi Abbas, Ge Yufeng, Pitla Santosh, Schnable James

机构信息

Department of Biological Systems Engineering, University of Nebraska-Lincoln, Lincoln, NE, United States.

Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, NE, United States.

出版信息

Front Plant Sci. 2021 Jun 25;12:611940. doi: 10.3389/fpls.2021.611940. eCollection 2021.

Abstract

Phenotyping plants is an essential component of any effort to develop new crop varieties. As plant breeders seek to increase crop productivity and produce more food for the future, the amount of phenotype information they require will also increase. Traditional plant phenotyping relying on manual measurement is laborious, time-consuming, error-prone, and costly. Plant phenotyping robots have emerged as a high-throughput technology to measure morphological, chemical and physiological properties of large number of plants. Several robotic systems have been developed to fulfill different phenotyping missions. In particular, robotic phenotyping has the potential to enable efficient monitoring of changes in plant traits over time in both controlled environments and in the field. The operation of these robots can be challenging as a result of the dynamic nature of plants and the agricultural environments. Here we discuss developments in phenotyping robots, and the challenges which have been overcome and others which remain outstanding. In addition, some perspective applications of the phenotyping robots are also presented. We optimistically anticipate that autonomous and robotic systems will make great leaps forward in the next 10 years to advance the plant phenotyping research into a new era.

摘要

对植物进行表型分析是培育新作物品种的任何努力的重要组成部分。随着植物育种者努力提高作物产量并为未来生产更多粮食,他们所需的表型信息数量也会增加。依靠人工测量的传统植物表型分析既费力、耗时、容易出错,成本又高。植物表型分析机器人已成为一种高通量技术,用于测量大量植物的形态、化学和生理特性。已经开发了几种机器人系统来完成不同的表型分析任务。特别是,机器人表型分析有潜力在可控环境和田间高效监测植物性状随时间的变化。由于植物和农业环境的动态性质,这些机器人的操作可能具有挑战性。在此,我们讨论表型分析机器人的发展情况,以及已经克服的挑战和仍然存在的突出问题。此外,还介绍了表型分析机器人的一些潜在应用。我们乐观地预计,自主和机器人系统将在未来10年取得巨大进展,推动植物表型分析研究进入一个新时代。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/61b0/8267384/79a4fe65b4c4/fpls-12-611940-g001.jpg

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