Müller-Linow Mark, Wilhelm Jens, Briese Christoph, Wojciechowski Tobias, Schurr Ulrich, Fiorani Fabio
1IBG-2: Plant Sciences, Institute for Bio- and Geosciences, Forschungszentrum Jülich, 52425 Jülich, Germany.
2Present Address: German Aerospace Center (DLR), Lilienthalplatz 7, 38108 Brunswick, Germany.
Plant Methods. 2019 Jan 11;15:2. doi: 10.1186/s13007-019-0386-z. eCollection 2019.
The development of leaf area is one of the fundamental variables to quantify plant growth and physiological function and is therefore widely used to characterize genotypes and their interaction with the environment. To date, analysis of leaf area often requires elaborate and destructive measurements or imaging-based methods accompanied by automation that may result in costly solutions. Consequently in recent years there is an increasing trend towards simple and affordable sensor solutions and methodologies. A major focus is currently on harnessing the potential of applications developed for smartphones that provide access to analysis tools to a wide user basis. However, most existing applications entail significant manual effort during data acquisition and analysis.
With the development of we provide a suitable smartphone solution for estimating digital proxies of leaf area and biomass in various imaging scenarios in the lab, greenhouse and in the field. To distinguish between plant tissue and background the core of the application comprises different classification approaches that can be parametrized by users delivering results on-the-fly. We demonstrate the practical applications of computing projected leaf area based on two case studies with and plants. These studies showed highly significant correlations with destructive measurements of leaf area and biomass from both ground truth measurements and estimations from well-established screening systems.
We show that a smartphone together with our analysis tool is a suitable platform for rapid quantification of leaf and shoot development of various plant architectures. Beyond the estimation of projected leaf area the app can also be used to quantify color and shape parameters of other plant material including seeds and flowers.
叶面积的发展是量化植物生长和生理功能的基本变量之一,因此被广泛用于表征基因型及其与环境的相互作用。迄今为止,叶面积分析通常需要精细且具有破坏性的测量方法,或者基于成像且需要自动化辅助的方法,这可能会导致成本高昂。因此,近年来,人们越来越倾向于采用简单且经济实惠的传感器解决方案和方法。目前的一个主要重点是挖掘为智能手机开发的应用程序的潜力,这些应用程序能为广大用户提供分析工具。然而,大多数现有应用程序在数据采集和分析过程中需要大量的人工操作。
随着[具体内容未给出]的发展,我们提供了一种合适的智能手机解决方案,用于在实验室、温室和田间的各种成像场景中估算叶面积和生物量数字代理。为了区分植物组织和背景,该应用程序的核心包括不同的分类方法,用户可以对其进行参数设置并即时获得结果。我们基于对[具体植物未给出]和[具体植物未给出]植物的两个案例研究,展示了计算投影叶面积的实际应用。这些研究表明,与基于实地测量以及成熟筛选系统估算的叶面积和生物量的破坏性测量结果具有高度显著的相关性。
我们表明,智能手机与我们的分析工具[具体工具未给出]一起,是快速量化各种植物结构中叶和茎发育的合适平台。除了估算投影叶面积外,该应用程序还可用于量化包括种子和花朵在内的其他植物材料的颜色和形状参数。