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Information Technologies in Environmental Engineering pp 238–251Cite as

Plant Phenotyping with Low Cost Digital Cameras and Image Analytics

Part of the Environmental Science and Engineering book series (ENVENG)

Abstract

In this paper we discuss a prototype, easy-to-deploy, and low cost (∼ $250) phenotype collection system for growth chambers. Off the shelf digital cameras, wireless transmitters, and PCs are used to store and process the images. A Matlab pipeline is used to fuse multiple images, identify the location of each Arabidopsis plant, segment its leaves, and measure leaf topology and area. Our early findings (unpublished) using this system for correlating genotype to phenotype are very promising. We hope that with future improvements and broad adoption, it will have the same disruptive effects as the first “build your own” microarrayers, which allowed for the explosion of genotyping information. Low cost genotyping and phenotyping will hopefully address some of the environmental, agricultural, and industrial sustainability challenges we are facing today.

Keywords

  • Image Fusion
  • Complex Biological System
  • Soil Water Deficit
  • Phenotyping System
  • Image Processing Module

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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  • DOI: 10.1007/978-3-540-88351-7_18
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Acknowledgements

We would like to thank Prof. Borevitz (Department of Ecology and Evolution at University of Chicago) for providing us with the images and initial funding for this effort. Finally, we should thank Ron Hause, a graduate student from the Committee on Genetics, Genomics, and Systems Biology who did his rotation in Prof. Borevitz’s Lab, for his assistance in the development of this project.

Author information

Authors and Affiliations

  1. Department of Electrical Engineering and Computer Science, Northwestern University Evanston, IL, US

    Sotirios A Tsaftaris

  2. Ecology and Evolution Department, University of Chicago, Chicago, IL, US

    Christos Noutsos

Authors
  1. Sotirios A Tsaftaris
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  2. Christos Noutsos
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Editor information

Editors and Affiliations

  1. Istituto Dalle Molle di Studi sull’Intelligenza Artificiale (IDSIA), Galleria 2, 6928, Manno, Switzerland

    Dr. Ioannis N. Athanasiadis & Prof. Andrea E. Rizzoli & 

  2. Aristotle University of Thessaloniki, Greece

    Pericles A. Mitkas

  3. Fak. Informatik Abt. Wirtschaftsinformatik, Universität Oldenburg, Ammerländer Heerstr. 114-118, 26129, Oldenburg, Germany

    Prof. Dr.-Ing. Jorge Marx Gómez

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Tsaftaris, S.A., Noutsos, C. (2009). Plant Phenotyping with Low Cost Digital Cameras and Image Analytics. In: Athanasiadis, I.N., Rizzoli, A.E., Mitkas, P.A., Gómez, J.M. (eds) Information Technologies in Environmental Engineering. Environmental Science and Engineering(). Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88351-7_18

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