Literature DB >> 35895199

Using Cameras for Precise Measurement of Two-Dimensional Plant Features: CASS.

Amy Tabb1, Germán A Holguín2, Rachel Naegele3.   

Abstract

Images are used frequently in plant phenotyping to capture measurements. This chapter offers a repeatable method for capturing two-dimensional measurements of plant parts in field or laboratory settings using a variety of camera styles (cellular phone, DSLR), with the addition of a printed calibration pattern. The method is based on calibrating the camera using information available from the EXIF tags from the image, as well as visual information from the pattern. Code is provided to implement the method, as well as a dataset for testing. We include steps to verify protocol correctness by imaging an artifact. The use of this protocol for two-dimensional plant phenotyping will allow data capture from different cameras and environments, with comparison on the same physical scale. We abbreviate this method as CASS, CAmera aS Scanner.
© 2022. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.

Entities:  

Keywords:  Camera calibration; Image measurement; Plant phenotyping

Mesh:

Year:  2022        PMID: 35895199     DOI: 10.1007/978-1-0716-2537-8_10

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  7 in total

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3.  Morphometrics Reveals Complex and Heritable Apple Leaf Shapes.

Authors:  Zoë Migicovsky; Mao Li; Daniel H Chitwood; Sean Myles
Journal:  Front Plant Sci       Date:  2018-01-04       Impact factor: 5.753

4.  Digital Morphometrics of Two North American Grapevines (Vitis: Vitaceae) Quantifies Leaf Variation between Species, within Species, and among Individuals.

Authors:  Laura L Klein; Madeleine Caito; Chad Chapnick; Cassandra Kitchen; Regan O'Hanlon; Dan H Chitwood; Allison J Miller
Journal:  Front Plant Sci       Date:  2017-03-17       Impact factor: 5.753

5.  Topological Data Analysis as a Morphometric Method: Using Persistent Homology to Demarcate a Leaf Morphospace.

Authors:  Mao Li; Hong An; Ruthie Angelovici; Clement Bagaza; Albert Batushansky; Lynn Clark; Viktoriya Coneva; Michael J Donoghue; Erika Edwards; Diego Fajardo; Hui Fang; Margaret H Frank; Timothy Gallaher; Sarah Gebken; Theresa Hill; Shelley Jansky; Baljinder Kaur; Phillip C Klahs; Laura L Klein; Vasu Kuraparthy; Jason Londo; Zoë Migicovsky; Allison Miller; Rebekah Mohn; Sean Myles; Wagner C Otoni; J C Pires; Edmond Rieffer; Sam Schmerler; Elizabeth Spriggs; Christopher N Topp; Allen Van Deynze; Kuang Zhang; Linglong Zhu; Braden M Zink; Daniel H Chitwood
Journal:  Front Plant Sci       Date:  2018-04-25       Impact factor: 5.753

6.  Image-based phenotyping for identification of QTL determining fruit shape and size in American cranberry (Vaccinium macrocarpon L.).

Authors:  Luis Diaz-Garcia; Giovanny Covarrubias-Pazaran; Brandon Schlautman; Edward Grygleski; Juan Zalapa
Journal:  PeerJ       Date:  2018-08-15       Impact factor: 2.984

7.  Digital imaging of root traits (DIRT): a high-throughput computing and collaboration platform for field-based root phenomics.

Authors:  Abhiram Das; Hannah Schneider; James Burridge; Ana Karine Martinez Ascanio; Tobias Wojciechowski; Christopher N Topp; Jonathan P Lynch; Joshua S Weitz; Alexander Bucksch
Journal:  Plant Methods       Date:  2015-11-02       Impact factor: 4.993

  7 in total

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