PlantCV: A Modular Image Analysis Toolkit for Building Plant Phenotyping Workflows

CyVerse Webinar

With the push towards precision agriculture to solve urgent global food production and climate change challenges we are facing, plant biologists and computational scientists now have more tools than ever, like PlantCV, to do image-based plant phenotyping within their own research program. Presenter Noah Fahlgren, one of the creators of Plant Computer Vision (PlantCV), gives an overview of how PlantCV is built, what research can be done with PlantCV, and how users can apply it to their own projects. He explains some of the built-in tools that include traditional image analysis and machine learning methods, and how these can be combined with other image analysis tools from the Python community. Noah then demonstrates how to build your own image analysis workflows on your laptop, on your own servers, or on CyVerse using VICE. If you've ever wanted to do image-based plant (or other organisms!) phenotyping, this webinar will show you that image-based analysis in your research is achievable and that you do not need an expensive system for imaging to get started now!

Webinar materials, including interactive slides, are available here: https://cyverse.org/webinar-plantcv-image-analysis-toolkit-for-building-plant-phenotyping-workflows 

Noah Fahlgren

Noah Fahlgren is the Director of the Data Science group at the Donald Danforth Plant Science Center. The Data Science group works at the intersection of plant science and computational sciences. In particular, the group develops data management and analysis software and approaches for proximal and remote sensing of plants. These tools are used to quantitatively measure plant phenotypes and responses to the environment for applications in foundational research, breeding, and precision agriculture.

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An introduction to image analysis workflows with PlantCV

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Raspberry Pi-powered imaging and open source software for plant phenotyping