Using R based image analysis to quantify rust on perennial ryegrass

Loading...
Thumbnail Image

Persistent link to this item

Statistics
View Statistics

Journal Title

Journal ISSN

Volume Title

Title

Using R based image analysis to quantify rust on perennial ryegrass

Published Date

2018-11

Publisher

Type

Presentation

Abstract

Crown and stem rust caused by Puccinia coronata f. sp. lolii and Puccinia graminis subsp. graminicola are major diseases of perennial ryegrass (Lolium perenne L.) when grown for turfgrass, forage, and seed. Plant breeders and pathologists often quantify rust severity in the field using the modified Cobb scale, but this method is subjective, labor intensive, and dependent on the skill and experience of the scorer. Our objective was to develop a novel, open-source system that couples both ImageJ and R to quantify rust severity on simple RGB images.

Description

Poster presented at the 2018 ASA and CSSA Annual Meeting, Nov. 4-7 in Baltimore, MD

Related to

Replaces

License

Series/Report Number

Funding information

Isbn identifier

Doi identifier

Previously Published Citation

Other identifiers

Suggested citation

Heineck, Garett; Watkins, Eric; Jungers, Jacob; McNish, Ian. (2018). Using R based image analysis to quantify rust on perennial ryegrass. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/214350.

Content distributed via the University Digital Conservancy may be subject to additional license and use restrictions applied by the depositor. By using these files, users agree to the Terms of Use. Materials in the UDC may contain content that is disturbing and/or harmful. For more information, please see our statement on harmful content in digital repositories.