Literature DB >> 15078337

Automatic quantification of morphological traits via three-dimensional measurement of Arabidopsis.

Eli Kaminuma1, Naohiko Heida, Yuko Tsumoto, Naoki Yamamoto, Nobuharu Goto, Naoki Okamoto, Akihiko Konagaya, Minami Matsui, Tetsuro Toyoda.   

Abstract

Many mutants have been isolated from the model plant Arabidopsis thaliana, and recent important genetic resources, such as T-DNA knockout lines, facilitate the speed of identifying new mutants. However, present phenotypic analysis of mutant screens depends mainly on qualitative descriptions after visual observation of morphological traits. We propose a novel method of phenotypic analysis based on precise three-dimensional (3D) measurement by a laser range finder (LRF) and automatic data processing. We measured the 3D surfaces of young plants of two Arabidopsis ecotypes and successfully defined two new traits, the direction of the blade surface and epinasty of the blade, quantitatively. The proposed method enables us to obtain quantitative and precise descriptions of plant morphologies compared to conventional 2D measurement. The method will open a way to find new traits from mutant pools or natural ecotypes based on 3D data.

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Year:  2004        PMID: 15078337     DOI: 10.1111/j.1365-313X.2004.02042.x

Source DB:  PubMed          Journal:  Plant J        ISSN: 0960-7412            Impact factor:   6.417


  7 in total

1.  Quantifying Shape Changes and Tissue Deformation in Leaf Development.

Authors:  Anne-Gaëlle Rolland-Lagan; Lauren Remmler; Camille Girard-Bock
Journal:  Plant Physiol       Date:  2014-04-07       Impact factor: 8.340

2.  Hyperspectral imaging techniques for rapid identification of Arabidopsis mutants with altered leaf pigment status.

Authors:  Osamu Matsuda; Ayako Tanaka; Takao Fujita; Koh Iba
Journal:  Plant Cell Physiol       Date:  2012-04-01       Impact factor: 4.927

3.  Limits of active laser triangulation as an instrument for high precision plant imaging.

Authors:  Stefan Paulus; Thomas Eichert; Heiner E Goldbach; Heiner Kuhlmann
Journal:  Sensors (Basel)       Date:  2014-02-05       Impact factor: 3.576

4.  Automatic Non-Destructive Growth Measurement of Leafy Vegetables Based on Kinect.

Authors:  Yang Hu; Le Wang; Lirong Xiang; Qian Wu; Huanyu Jiang
Journal:  Sensors (Basel)       Date:  2018-03-07       Impact factor: 3.576

5.  All roads lead to growth: imaging-based and biochemical methods to measure plant growth.

Authors:  Justyna Jadwiga Olas; Franziska Fichtner; Federico Apelt
Journal:  J Exp Bot       Date:  2020-01-01       Impact factor: 6.992

6.  Terrestrial 3D laser scanning to track the increase in canopy height of both monocot and dicot crop species under field conditions.

Authors:  Michael Friedli; Norbert Kirchgessner; Christoph Grieder; Frank Liebisch; Michael Mannale; Achim Walter
Journal:  Plant Methods       Date:  2016-01-29       Impact factor: 4.993

7.  Automatic Leaf Segmentation for Estimating Leaf Area and Leaf Inclination Angle in 3D Plant Images.

Authors:  Kenta Itakura; Fumiki Hosoi
Journal:  Sensors (Basel)       Date:  2018-10-22       Impact factor: 3.576

  7 in total

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