Dataset for: A rapid, semi-automated image-based method for quantitative assessment of rust disease progression in wheat

Data supporting the development and validation of RONUM, an ImageJ-based workflow for semi-automated quantification of wheat leaf rust (Puccinia triticina), and associated whole-plant and detached-leaf infection assays. This repository contains image datasets and source data used for validation and demonstration of the methods described in the associated publication. Image datasets include scanned-leaf and detached-leaf validation images with manually corrected reference masks, whole-plant disease progression scans, detached-leaf disease progression images, differential wheat-line images, inoculum optimisation images, and images from a propiconazole dose-response experiment. RONUM_DATA_SUMMARY.xlsx contains the principal numerical source data underlying the validation and application analyses, including scanned- and detached-leaf validation, disease progression, differential-line phenotyping, particle measurements, and the propiconazole dose-response experiment. RONUM source code, documentation and current releases are available through the associated GitHub repository.Feel free to reach out for additional info or images. chris.mann@uq.edu.au