Department of Telecommunications and Information Processing, Ghent University, 9000 Ghent, Belgium.
Plant Physiol. 2012 Nov;160(3):1149-59. doi: 10.1104/pp.112.202762. Epub 2012 Aug 31.
Image analysis of Arabidopsis (Arabidopsis thaliana) rosettes is an important nondestructive method for studying plant growth. Some work on automatic rosette measurement using image analysis has been proposed in the past but is generally restricted to be used only in combination with specific high-throughput monitoring systems. We introduce Rosette Tracker, a new open source image analysis tool for evaluation of plant-shoot phenotypes. This tool is not constrained by one specific monitoring system, can be adapted to different low-budget imaging setups, and requires minimal user input. In contrast with previously described monitoring tools, Rosette Tracker allows us to simultaneously quantify plant growth, photosynthesis, and leaf temperature-related parameters through the analysis of visual, chlorophyll fluorescence, and/or thermal infrared time-lapse sequences. Freely available, Rosette Tracker facilitates the rapid understanding of Arabidopsis genotype effects.
拟南芥(Arabidopsis thaliana)莲座丛的图像分析是研究植物生长的一种重要的非破坏性方法。过去已经提出了一些使用图像分析进行自动莲座丛测量的工作,但通常仅限于与特定的高通量监测系统结合使用。我们引入了 Rosette Tracker,这是一种新的开源图像分析工具,用于评估植物冠层表型。该工具不受特定监测系统的限制,可以适应不同的低预算成像设置,并且只需要最少的用户输入。与以前描述的监测工具相比,Rosette Tracker 允许我们通过分析视觉、叶绿素荧光和/或热红外时间推移序列来同时量化植物生长、光合作用和叶片温度相关参数。Rosette Tracker 免费提供,方便快速理解拟南芥基因型的影响。