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Plantcv V2: Image Analysis Software For High-Throughput Plant Phenotyping, Malia A. Gehan, Noah Fahlgren, Arash Abbasi, Jeffrey C. Berry, Steven T. Callen, Leonardo Chavez, Andrew N. Doust, Max J. Feldman, Kerrigan B. Gilbert, John G. Hodge, J. Steen Hoyer, Andy Lin, Suxing Liu, César Lizárraga, Argelia Lorence, Michael Miller, Eric Platon, Monica Tessman, Tony Sax

Department of Agronomy and Horticulture: Faculty Publications

Systems for collecting image data in conjunction with computer vision techniques are a powerful tool for increasing the temporal resolution at which plant phenotypes can be measured non-destructively. Computational tools that are flexible and extendable are needed to address the diversity of plant phenotyping problems. We previously described the Plant Computer Vision (PlantCV) software package, which is an image processing toolkit for plant phenotyping analysis. The goal of the PlantCV project is to develop a set of modular, reusable, and repurposable tools for plant image analysis that are open-source and community-developed. Here we present the details and rationale for major …