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Zierold U, Scholz U, Schweizer P. Transcriptome analysis of mlo-mediated resistance in the epidermis of barley. Mol Plant Pathol. 2005;6:139–151.
Douchkov D, Lück S, Johrde A, Nowara D, Himmelbach A, Rajaraman J, Stein N, Sharma R, Kilian B, Schweizer P. Discovery of genes affecting resistance of barley to adapted and non-adapted powdery mildew fungi. Genome Biol. 2014;15(12):518.
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Brehar R, Mitrea DA, Vancea F, Marita T, Nedevschi S, Lupsor-Platon M, Rotaru M, Badea RI. Comparison of deep-learning and conventional machine-learning methods for the automatic recognition of the hepatocellular carcinoma areas from ultrasound images. Sensors. 2020;20:3085.
Kuska MT, Heim MT, Geedicke, Heim RHJ, Geedicke I, Gold KM, Brugger A, Paulus S. Digital plant pathology: A foundation and guide to modern agriculture. J Plant Dis Prot. 2022;129(3):457–468.
Lück S, Strickert M, Lorbeer M, Melchert F, Backhaus A, Kilias D, Seiffert U, Douchkov D. “Macrobot”: An automated segmentation-based system for powdery mildew disease quantification. Plant Phenomics. 2020;2020:5839856.
Hinterberger V, Douchkov D, Lück S, Kale S, Mascher M, Stein N, Reif JC, Schulthess AW. Mining for new sources of resistance to powdery mildew in genetic resources of winter wheat. Front Plant Sci. 2022;13:836723.
Saleem K, Hovmøller MS, Labouriau R, Justesen AF, Orabi J, Andersen JR, Sorensen CK. Macroscopic and microscopic phenotyping using diverse yellow rust races increased the resolution of seedling and adult plant resistance in wheat breeding lines. MDPI Agronomy. 2015;53:445–470.
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