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PhenoImage: an open-source GUI for plant image analysis

Feiyu Zhu, Manny Saluja, Jaspinder Singh, View ORCID ProfilePuneet Paul, View ORCID ProfileScott E. Sattler, Paul Staswick, View ORCID ProfileHarkamal Walia, Hongfeng Yu
doi: https://doi.org/10.1101/2020.09.01.278234
Feiyu Zhu
1Department of Computer Science and Engineering, University of Nebraska-Lincoln, USA
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Manny Saluja
2Department of Agronomy and Horticulture, University of Nebraska-Lincoln, USA
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Jaspinder Singh
2Department of Agronomy and Horticulture, University of Nebraska-Lincoln, USA
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Puneet Paul
2Department of Agronomy and Horticulture, University of Nebraska-Lincoln, USA
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  • ORCID record for Puneet Paul
Scott E. Sattler
2Department of Agronomy and Horticulture, University of Nebraska-Lincoln, USA
3Wheat, Sorghum and Forage Research Unit, USDA-ARS, Lincoln, NE, USA
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Paul Staswick
2Department of Agronomy and Horticulture, University of Nebraska-Lincoln, USA
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Harkamal Walia
2Department of Agronomy and Horticulture, University of Nebraska-Lincoln, USA
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  • ORCID record for Harkamal Walia
Hongfeng Yu
1Department of Computer Science and Engineering, University of Nebraska-Lincoln, USA
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  • For correspondence: hfyu@unl.edu
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Abstract

High-throughput genotyping coupled with molecular breeding approaches has dramatically accelerated crop improvement programs. More recently, improved plant phenotyping methods have led to a shift from manual measurements to automated platforms with increased scalability and resolution. Considerable effort has also gone into the development of large-scale downstream processing of the imaging datasets derived from high-throughput phenotyping (HTP) platforms. However, most available tools require some programing skills. We developed PhenoImage – an open-source GUI based cross-platform solution for HTP image processing with the aim to make image analysis accessible to users with either little or no programming skills. The open-source nature provides the possibility to extend its usability to meet user-specific requirements. The availability of multiple functions and filtering parameters provides flexibility to analyze images from a wide variety of plant species and platforms. PhenoImage can be run on a personal computer as well as on high-performance computing clusters. To test the efficacy of the application, we analyzed the LemnaTec Imaging system derived RGB and fluorescence shoot images from two plant species: sorghum and wheat differing in their physical attributes. In the study, we discuss the development, implementation, and working of the PhenoImage.

Highlight PhenoImage is an open-source application designed for analyzing images derived from high-throughput phenotyping.

  • high-throughput phenotyping
  • image processing
  • plant phenotyping
  • RGB images
  • fluorescence images
  • sorghum
  • wheat

Footnotes

  • Others: FZ: feiyuzhu520{at}gmail.com, MS: saluja.manny12{at}gmail.com, JS: jaspinderjawandha75{at}gmail.com, PP: puneet6288{at}gmail.com, SS: scott.sattler{at}usda.gov, PS: pstaswick1{at}unl.edu, HW: hwalia2{at}unl.edu

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-ND 4.0 International license.
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Posted September 02, 2020.
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PhenoImage: an open-source GUI for plant image analysis
Feiyu Zhu, Manny Saluja, Jaspinder Singh, Puneet Paul, Scott E. Sattler, Paul Staswick, Harkamal Walia, Hongfeng Yu
bioRxiv 2020.09.01.278234; doi: https://doi.org/10.1101/2020.09.01.278234
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PhenoImage: an open-source GUI for plant image analysis
Feiyu Zhu, Manny Saluja, Jaspinder Singh, Puneet Paul, Scott E. Sattler, Paul Staswick, Harkamal Walia, Hongfeng Yu
bioRxiv 2020.09.01.278234; doi: https://doi.org/10.1101/2020.09.01.278234

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