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

Abstract Background Rapid and objective assessment of foliar disease is important for screening host responses and evaluating novel control agents. We developed a complementary suite of low-cost methods for quantitative assessment of wheat leaf rust, combining an ImageJ-based disease quantification workflow (RONUM) with detached-leaf and soil-free whole-plant infection assays. Results RONUM enabled semi-automated quantification of disease metrics following user-guided calibration. Against manually corrected reference image sets from whole plant leaf scans and detached leaves, disease estimates showed strong agreement with reference measurements and were reproducible following independent calibration by multiple users, and by pixel agreement optimisation to the reference masks. Benchmarked against another published ImageJ workflow, RONUM also showed closer agreement with manually corrected measurements, particularly for images containing chlorosis, necrosis or poor leaf health. Post-processing options were quantitatively assessed, showing little influence over total pustule-area estimates but substantial effects upon pustule count estimates. Two complementary infection assays were presented to demonstrate example applications of the quantification workflow: a soil-free whole-plant assay for non-destructive tracking of leaf rust development over an 18-day infection time course; and a benchtop-scale detached-leaf assay. The detached leaf assay provided reproducible disease quantification across 13 wheat lines with contrasting disease phenotypes. Exploratory quantification of chlorosis: pustule area ratios substantially separated the susceptible lines from those harbouring pathotype-specific Lr resistance, showcasing a potential application for collecting biologically relevant phenotype data typically unavailable to image-based quantitation. Finally, a modified detached leaf assay with nylon-mesh treatment reservoir was developed and assessed by establishing a dose-response curve to a propiconazole fungicide formulation, with an estimated IC₅₀ of 20.49 ppm formulation (95% CI 14.64–28.11 ppm). Conclusions These methods provide accessible tools for quantitative wheat rust research using standard laboratory equipment and freely available software. The principal value of RONUM lies in flexible calibration to individual experimental systems followed by rapid and consistent quantification across replicate datasets, along with requisite annotation and output summaries for streamlined record keeping. Combined with complementary whole-plant and detached-leaf assays, the workflow enables quantitative assessment of disease progression, and the screening of candidate treatments or putative traits. While further validation is required, the preliminary application of these tools highlights potential application toward image-based characterisation of agronomically important traits.