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PlantCV v2.0: Image analysis software for high-throughput plant phenotyping

, , , , , , , , , , , , , , , , , ,
1 Donald Danforth Plant Science Center, St. Louis, Missouri, United States of America
2 Current Address: Monsanto Company, St. Louis, Missouri, United States of America
3 Department of Plant Biology, Ecology, and Evolution, Oklahoma State University, Stillwater, Oklahoma, United States of America
4 Computational and Systems Biology Program, Washington University in St. Louis, St. Louis, Missouri, United States of America
5 Current Address: Unidev, St. Louis, Missouri, United States of America
6 Arkansas Biosciences Institute, Arkansas State University, Jonesboro, Arkansas, United States of America
7 Current Address: Department of Plant Biology, University of Georgia, Athens, Georgia, United States of America
8 Current Address: CiBO Technologies, Cambridge, Massachusetts, United States of America
9 Arkansas Biosciences Institute, Department of Chemistry and Physics, Arkansas State University, Jonesboro, Arkansas, United States of America
10 Current Address: Department of Agronomy and Horticulture, Center for Plant Science Innovation, Beadle Center for Biotechnology, University of Nebraska - Lincoln, Lincoln, Nebraska, United States of America
11 Cosmos X, Tokyo, Japan
12 Missouri University of Science and Technology, Rolla, Missouri, United States of America
DOI
10.7287/peerj.preprints.3225v1
Published
Accepted
Subject Areas
Agricultural Science, Bioinformatics, Computational Biology, Plant Science, Data Mining and Machine Learning
Keywords
plant phenotyping, image analysis, computer vision, machine learning, morphometrics
Copyright
© 2017 Gehan et al.
Licence
This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Preprints) and either DOI or URL of the article must be cited.
Cite this article
Gehan MA, Fahlgren N, Abbasi A, Berry JC, Callen ST, Chavez L, Doust AN, Feldman MJ, Gilbert KB, Hodge JG, Hoyer JS, Lin A, Liu S, Lizárraga C, Lorence A, Miller M, Platon E, Tessman M, Sax T. 2017. PlantCV v2.0: Image analysis software for high-throughput plant phenotyping. PeerJ Preprints 5:e3225v1

Abstract

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 developments in the second major release of PlantCV. In addition to overall improvements in the organization of the PlantCV project, new functionality includes a set of new image processing and normalization tools, support for analyzing images that include multiple plants, leaf segmentation, landmark identification tools for morphometrics, and modules for machine learning.

Author Comment

This is a preprint submission to PeerJ Preprints. We intend to submit this preprint to PeerJ for peer review.

Additional Information

Competing Interests

Malia A Gehan, Noah Fahlgren, Arash Abbasi, Jeffrey C Berry, Steven T Callen, Leonardo Chavez, Max J Feldman, Kerrigan B Gilbert, Steen Hoyer, Andy Lin, César Lizárraga, Michael Miller and Monica Tessman contributed to the research described while working at the Donald Danforth Plant Science Center, a 501(c)(3) nonprofit research institute. Suxing Liu and Argelia Lorence contributed to the research described while working at the University of Arkansas. John G Hodge and Andrew N Doust contributed to the research described while working at the University of Oklahoma. Eric Platon contributed to the research described while working as a founder and employee of Cosmos X. Tony Sax contributed to the research described while a full-time student at the Missouri University of Science and Technology.

Author Contributions

Malia A Gehan conceived and designed the experiments, performed the experiments, analyzed the data, contributed reagents/materials/analysis tools, wrote the paper, prepared figures and/or tables, reviewed drafts of the paper.

Noah Fahlgren conceived and designed the experiments, performed the experiments, analyzed the data, contributed reagents/materials/analysis tools, wrote the paper, prepared figures and/or tables, reviewed drafts of the paper.

Arash Abbasi contributed reagents/materials/analysis tools, wrote the paper, reviewed drafts of the paper.

Jeffrey C Berry contributed reagents/materials/analysis tools, reviewed drafts of the paper.

Steven T Callen analyzed the data, contributed reagents/materials/analysis tools, wrote the paper, reviewed drafts of the paper.

Leonardo Chavez contributed reagents/materials/analysis tools, reviewed drafts of the paper.

Andrew N Doust contributed reagents/materials/analysis tools, wrote the paper, reviewed drafts of the paper.

Max J Feldman conceived and designed the experiments, performed the experiments, analyzed the data, contributed reagents/materials/analysis tools, wrote the paper, prepared figures and/or tables, reviewed drafts of the paper.

Kerrigan B Gilbert prepared figures and/or tables, reviewed drafts of the paper.

John G Hodge contributed reagents/materials/analysis tools, wrote the paper, reviewed drafts of the paper.

J Steen Hoyer performed the experiments, contributed reagents/materials/analysis tools, wrote the paper, reviewed drafts of the paper.

Andy Lin contributed reagents/materials/analysis tools, reviewed drafts of the paper.

Suxing Liu conceived and designed the experiments, contributed reagents/materials/analysis tools, wrote the paper, reviewed drafts of the paper.

César Lizárraga contributed reagents/materials/analysis tools, reviewed drafts of the paper.

Argelia Lorence conceived and designed the experiments, contributed reagents/materials/analysis tools, wrote the paper, reviewed drafts of the paper.

Michael Miller contributed reagents/materials/analysis tools, reviewed drafts of the paper.

Eric Platon contributed reagents/materials/analysis tools, reviewed drafts of the paper.

Monica Tessman contributed reagents/materials/analysis tools, reviewed drafts of the paper.

Tony Sax contributed reagents/materials/analysis tools, reviewed drafts of the paper.

Data Deposition

The following information was supplied regarding data availability:

PlantCV is available on GitHub at https://github.com/danforthcenter/plantcv. PlantCV v2.0 is archived on Zenodo at https://doi.org/10.5281/zenodo.854674. Scripts used for image and statistical analysis are available on GitHub at https://github.com/danforthcenter/plantcv-v2-paper.

Funding

This work was supported by the Donald Danforth Plant Science Center, the US National Science Foundation (IIA-1430427, IIA-1430428, IIA-1355406, IOS-1202682, MCB-1330562, and DBI-1156581), the US Department of Energy (DE-AR0000594, DE-SC0014395), and the US Department of Agriculture (MOW-2012-01361 and 2016-67009-25639). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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PlantCV v2.0: Image analysis software for high-throughput plant phenotyping
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