PT - JOURNAL ARTICLE AU - Zhu, Feiyu AU - Saluja, Manny AU - Singh, Jaspinder AU - Paul, Puneet AU - Sattler, Scott E. AU - Staswick, Paul AU - Walia, Harkamal AU - Yu, Hongfeng TI - <em>PhenoImage</em>: an open-source GUI for plant image analysis AID - 10.1101/2020.09.01.278234 DP - 2020 Jan 01 TA - bioRxiv PG - 2020.09.01.278234 4099 - http://biorxiv.org/content/early/2020/09/02/2020.09.01.278234.short 4100 - http://biorxiv.org/content/early/2020/09/02/2020.09.01.278234.full AB - 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.