TraineR2 is another Shiny app developed to train users in assessing disease severity, expressed as the percentage of the organ (leaf or fruit) affected by lesions. However, this app distinguishes itself by basing its assessments on actual photographs of disease symptoms.
TraineR2 is an enhancement of TraineR (see context here), sharing the same goal - facilitating the training of plant pathologists in estimating plant disease severity. The primary distinction lies in TraineR2’s utilization of actual photographs of disease symptoms, offering a more authentic representation compared to the computer-generated imagery used in TraineR. Additionally, the duration of the training session in TraineR2 is determined by the number of images available in the collection, presenting another noteworthy difference.
The objective of TraineR is to enhance the accuracy of prospective raters in estimating disease severity, based on the perceived percentage of the diseased area. At present, the app houses images of six plant diseases: Apple Glomerella leaf spot, citrus canker, eucalyptus Calonectria blight, gerbera Botrytis leaf blight, pecan scab, soybean rust, peanut leaf spot, and peach leaf rust. These images have been generously provided by colleagues in the plant pathology community and have been utilized in scientific papers for the validation of standard area diagram sets (SADs).
The app was developed in R + Shiny and was made available at the shinyapps.io pages.
This project is open to contributions of images from the community. Anyone interested in contributing should reach out to the app developer.
Project website: https://delponte.shinyapps.io/traineR2/
Author and maintainer: Emerson M. Del Ponte
If you see mistakes or want to suggest changes, please create an issue on the source repository.
Text and figures are licensed under Creative Commons Attribution CC BY 4.0. Source code is available at https://github.com/openplantpathology/OpenPlantPathology, unless otherwise noted. The figures that have been reused from other sources don't fall under this license and can be recognized by a note in their caption: "Figure from ...".