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高通量植物表型分析平台的陷阱与潜力

Pitfalls and potential of high-throughput plant phenotyping platforms.

作者信息

Poorter Hendrik, Hummel Grégoire M, Nagel Kerstin A, Fiorani Fabio, von Gillhaussen Philipp, Virnich Olivia, Schurr Ulrich, Postma Johannes A, van de Zedde Rick, Wiese-Klinkenberg Anika

机构信息

Plant Sciences (IBG-2), Forschungszentrum Jülich GmbH, Jülich, Germany.

Department of Natural Sciences, Macquarie University, North Ryde, NSW, Australia.

出版信息

Front Plant Sci. 2023 Aug 23;14:1233794. doi: 10.3389/fpls.2023.1233794. eCollection 2023.

DOI:10.3389/fpls.2023.1233794
PMID:37680357
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10481964/
Abstract

Automated high-throughput plant phenotyping (HTPP) enables non-invasive, fast and standardized evaluations of a large number of plants for size, development, and certain physiological variables. Many research groups recognize the potential of HTPP and have made significant investments in HTPP infrastructure, or are considering doing so. To make optimal use of limited resources, it is important to plan and use these facilities prudently and to interpret the results carefully. Here we present a number of points that users should consider before purchasing, building or utilizing such equipment. They relate to (1) the financial and time investment for acquisition, operation, and maintenance, (2) the constraints associated with such machines in terms of flexibility and growth conditions, (3) the pros and cons of frequent non-destructive measurements, (4) the level of information provided by proxy traits, and (5) the utilization of calibration curves. Using data from an Arabidopsis experiment, we demonstrate how diurnal changes in leaf angle can impact plant size estimates from top-view cameras, causing deviations of more than 20% over the day. Growth analysis data from another rosette species showed that there was a curvilinear relationship between total and projected leaf area. Neglecting this curvilinearity resulted in linear calibration curves that, although having a high r (> 0.92), also exhibited large relative errors. Another important consideration we discussed is the frequency at which calibration curves need to be generated and whether different treatments, seasons, or genotypes require distinct calibration curves. In conclusion, HTPP systems have become a valuable addition to the toolbox of plant biologists, provided that these systems are tailored to the research questions of interest, and users are aware of both the possible pitfalls and potential involved.

摘要

自动化高通量植物表型分析(HTPP)能够对大量植物的大小、发育情况和某些生理变量进行非侵入性、快速且标准化的评估。许多研究团队认识到HTPP的潜力,已对HTPP基础设施进行了大量投资,或者正在考虑这样做。为了优化利用有限资源,谨慎规划和使用这些设施并仔细解读结果非常重要。在此,我们提出一些用户在购买、建造或使用此类设备之前应考虑的要点。它们涉及:(1)购置、运行和维护所需的资金和时间投入;(2)此类机器在灵活性和生长条件方面的限制;(3)频繁进行非破坏性测量的利弊;(4)替代性状所提供信息的水平;(5)校准曲线的使用。利用拟南芥实验的数据,我们展示了叶角的昼夜变化如何影响顶视图相机对植物大小的估计,导致一天内偏差超过20%。来自另一种莲座状植物的生长分析数据表明,总叶面积和投影叶面积之间存在曲线关系。忽略这种曲线关系会导致线性校准曲线,尽管其r值较高(>0.92),但也表现出较大的相对误差。我们讨论的另一个重要考虑因素是生成校准曲线的频率,以及不同处理、季节或基因型是否需要不同的校准曲线。总之,只要HTPP系统是根据感兴趣的研究问题量身定制的,并且用户了解其中可能存在的陷阱和潜力,那么HTPP系统就已成为植物生物学家工具箱中一项有价值的补充。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a0bb/10481964/d06615762828/fpls-14-1233794-g008.jpg
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