TY - JOUR
T1 - PhenoImage
T2 - An open-source graphical user interface for plant image analysis
AU - Zhu, Feiyu
AU - Saluja, Manny
AU - Dharni, Jaspinder Singh
AU - Paul, Puneet
AU - Sattler, Scott E.
AU - Staswick, Paul
AU - Walia, Harkamal
AU - Yu, Hongfeng
N1 - Funding Information:
We thank the Nebraska Innovation Campus, University of Nebraska, Lincoln, for their support for the imaging experiments. This work was supported by National Science Foundation Award no. 1736192 to H. Walia and H. Yu, and by a gift to P. Staswick from Kamterter Products, LLC, Waverly, NE.
Publisher Copyright:
© 2021 The Authors. The Plant Phenome Journal published by Wiley Periodicals LLC on behalf of American Society of Agronomy and Crop Science Society of America.
PY - 2021
Y1 - 2021
N2 - High-throughput genotyping coupled with molecular breeding approaches have 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 developing large-scale downstream processing of the imaging datasets derived from high-throughput phenotyping (HTP) platforms. However, most available tools require some programming skills. We developed PhenoImage, an open-source graphical user interface (GUI) based cross-platform solution for HTP image processing intending 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 red, green, and blue (RGB) color intensity and plant pigmentation-based fluorescence shoot images from two plant species: sorghum [Sorghum bicolor (L.) Moench] and wheat (Triticum aestivum L.) differing in their physical attributes. In the study, we discuss the development, implementation, and working of the PhenoImage.
AB - High-throughput genotyping coupled with molecular breeding approaches have 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 developing large-scale downstream processing of the imaging datasets derived from high-throughput phenotyping (HTP) platforms. However, most available tools require some programming skills. We developed PhenoImage, an open-source graphical user interface (GUI) based cross-platform solution for HTP image processing intending 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 red, green, and blue (RGB) color intensity and plant pigmentation-based fluorescence shoot images from two plant species: sorghum [Sorghum bicolor (L.) Moench] and wheat (Triticum aestivum L.) differing in their physical attributes. In the study, we discuss the development, implementation, and working of the PhenoImage.
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U2 - 10.1002/ppj2.20015
DO - 10.1002/ppj2.20015
M3 - Article
AN - SCOPUS:85118999716
SN - 2578-2703
VL - 4
JO - Plant Phenome Journal
JF - Plant Phenome Journal
IS - 1
M1 - e20015
ER -