PlantCV v2: Image analysis software for high-throughput plant phenotyping | Zendy

Malia Gehan | Zendy; Noah Fahlgren | Zendy; Arash Abbasi | Zendy; Jeffrey C. Berry | Zendy; Steven T. Callen | Zendy; Leonardo Chavez | Zendy; Andrew N. Doust | Zendy; Max Feldman | Zendy; Kerrigan B. Gilbert | Zendy; John G. Hodge | Zendy; J. Steen Hoyer | Zendy; Andy Lin | Zendy; Suxing Liu | Zendy; César Lizárraga | Zendy; Argelia Lorence | Zendy; Michael D. Miller | Zendy; Éric Platon | Zendy; Monica Tessman | Zendy; Tony Sax | Zendy

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

Author(s) -

Malia Gehan,

Noah Fahlgren,

Arash Abbasi,

Jeffrey C. Berry,

Steven T. Callen,

Leonardo Chavez,

Andrew N. Doust,

Max Feldman,

Kerrigan B. Gilbert,

John G. Hodge,

J. Steen Hoyer,

Andy Lin,

Suxing Liu,

César Lizárraga,

Argelia Lorence,

Michael D. Miller,

Éric Platon,

Monica Tessman,

Tony Sax

Publication year - 2017

Publication title -

peerj

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.927

H-Index - 70

ISSN - 2167-8359

DOI - 10.7717/peerj.4088

Subject(s) - computer science , software , modular design , normalization (sociology) , image processing , segmentation , artificial intelligence , image analysis , identification (biology) , landmark , set (abstract data type) , plant identification , digital image processing , computer vision , data mining , image (mathematics) , programming language , botany , sociology , anthropology , biology

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.

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