Donald Danforth Plant Science Center

To Feed, Clothe, and Power the World in the Face of a Growing and Urbanizing World Population, We Need Technologies That Accelerate Plant Breeding and Crop Development Pipelines. Imaging and Remote Sensing Technologies, Coupled With Data Analytics, Aims to Increase the Throughput of Measuring Plant Physical and Physiological Features (phenotyping) by Enabling the Ability to Non-destructively Assay More Genetic Lineages at Higher Spatial and Temporal Resolution. While Many Tools and Algorithms Exist to Extract Information From Image Data, Use of Image Analysis Tools for Plant Phenotyping Is Still a Relatively New Field, and Many Existing Tools Are Either Created for Targeted Purposes or Are Poorly Maintained After Release. We Built the Open-source Plantcv Software Package to Address These Challenges and Our Goal Is to Provide a Common Interface for Plant Phenotyping Algorithms With the Aim to Build a Modular Platform That We and Others Could Build On.in This Project We Will Build on the Existing Plantcv Platform to Develop New Tools and Capabilities for Plant Phenotyping. in Particular, We Will Develop New Analysis Capabilities That Utilize Machine Learning for Automated Plant Feature Detection, and Broaden Support for New Types of Cameras and Sensors. a New Toolkit That Streamlines the Collection of Human-curated Data Used to Train Machine Learning Algorithms Will Enhance the Utility of the New Analysis Tools. a New Data and Computing Management System Will Improve the Ability of Users to Deploy Plant Phenotyping Tools on Diverse Systems at Infrastructure-scale. Opportunities for Training and Education of Stakeholders Will Be Provided Through Hands-on Workshops and Online, Interactive Documentation. Our Overall Goal, Which Aligns With the Food and Agriculture Cyberinformatics and Tools Program Area Priorities, Is to Build a Scalable Analysis and Data Integration Platform That Enables Stakeholders in the Plant Phenotyping Community to Effectively Utilize Data to Accelerate Discoveries in Plant Science and Agricultural Research.