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