Quite a few papers on quantitative resistance of Z. tritici used recently automated image analysis macro of ImageJ for measuring host damage and pathogen reproduction on wheat leaves [for example, 1, 2, 3]. The method was developed by Ethan Stewart in 2014 , improved in 2016 , and further developed by us in 2018 . We recently added a few unpublished improvements.
Since the introduction of the method, there have been changes in the operating systems, software and packages that the method is dependent on. Furthermore, the method was originally developed with and for MacOS only. For these reasons, people have faced challenges in installation and usage of the method. As we have developed the method further and succeeded in setting it up on Linux and Windows, we decided to put together our knowledge and tips on the installation and usage. Currently, instructions and installation files are available for MacOS (Sierra) and Windows (10). We also provide the most up-to-date version of the macro here.
We hope that these instructions will help the adoption of the method among scientists globally. Please report any issues and/or success in installing and using it, so that we can either help you resolving the issues or celebrate together with you.
With best wishes, Petteri Karisto and Alexey Mikaberidze
1. Stewart EL, Croll D, Lendenmann MH, Sanchez‐Vallet A, Hartmann FE, Palma‐Guerrero J, Ma X, Mcdonald BA. Quantitative trait locus mapping reveals complex genetic architecture of quantitative virulence in the wheat pathogen Zymoseptoria tritici. Molecular plant pathology. 2018; 19:201-16. doi:10.1111/mpp.12515
2. Meile L, Croll D, Brunner PC, Plissonneau C, Hartmann FE, McDonald BA, Sánchez‐Vallet A. A fungal avirulence factor encoded in a highly plastic genomic region triggers partial resistance to septoria tritici blotch. New Phytologist. 2018; 219:1048-1061. doi:10.1111/nph.15180
3. Karisto P, Hund A, Yu K, Anderegg J, Walter A, Mascher F, McDonald BA, Mikaberidze A. Ranking quantitative resistance to Septoria tritici blotch in elite wheat cultivars using automated image analysis. Phytopathology. 2018; 108:568-81. doi: 10.1094/PHYTO-04-17-0163-R. Open Access in bioRxiv, doi: 10.1101/129353.
4. Stewart EL, McDonald BA. Measuring quantitative virulence in the wheat pathogen Zymoseptoria tritici using high-throughput automated image analysis. Phytopathology. 2014; 104:985-92. doi: 10.1094/PHYTO-11-13-0328-R
5. Stewart EL, Hagerty CH, Mikaberidze A, Mundt CC, Zhong Z, McDonald BA. An improved method for measuring quantitative resistance to the wheat pathogen Zymoseptoria tritici using high-throughput automated image analysis. Phytopathology. 2016; 106:782-8. doi: 10.1094/PHYTO-01-16-0018-R