Using R based image analysis to quantify rust on perennial ryegrass
Loading...
View/Download File
Persistent link to this item
Statistics
View StatisticsJournal 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
Collections
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.