Rosette Tracker: An Open Source Image Analysis Tool for Automatic Quantification of Genotype Effects
Author(s) -
Jonas De Vylder,
Filip Vandenbussche,
Yuming Hu,
Wilfried Philips,
Dominique Van Der Straeten
Publication year - 2012
Publication title -
plant physiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.554
H-Index - 312
eISSN - 1532-2548
pISSN - 0032-0889
DOI - 10.1104/pp.112.202762
Subject(s) - rosette (schizont appearance) , arabidopsis , arabidopsis thaliana , biological system , biology , computational biology , open source , computer science , artificial intelligence , computer vision , genetics , mutant , software , programming language , gene , immunology
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.
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