Senior Computational Scientist Donald Danforth Plant Science Center
Disclosure: Disclosure information not submitted.
PlantCV is an open-source image analysis software package targeted for plant phenotyping. Traditional phenotyping is time consuming, costly, and often destructive, therefore streamlined processes will allow research to advance beyond this bottleneck. The PlantCV project was started at the Donald Danforth Plant Science Center in 2014, and is under active development. Core values of the project are open communication and collaboration among stakeholders from diverse backgrounds and areas of expertise. The mission of the PlantCV project is to provide a common interface for a collection of image analysis techniques, and utilize a modular architecture that enables flexibility in the design of analysis workflows and rapid integration of new methods. These tools provide a simplified interface for users to utilize underlying tools and build custom analysis workflows without significant experience with programming. Clear and extensive documentation is vital to this mission and is reflected in the currently available 11 static and the 13 interactive tutorials.
Common data that users extract while using PlantCV vary from shape, size, and color characteristics, NIR information, measures of fluorescence, and plant morphology information. White balancing and color correction tools using color cards allow users to standardize their dataset. Height, plant area, and other measures of shape are easily standardized in downstream data analysis with the PlantCV size marker tool. Recent tools added to the software include the ability to analyze thermal data, hyperspectral data, and morphological traits such as internode length, individual leaf length, measures of leaf curvature, and measures of leaf angle. The built in workflow parallelization tool allows users to execute a workflow across an entire dataset of images and gather data collected into a CSV file that can be imported into any preferred data analysis tool.
