Zymoseptoria tritici, the causal agent of septoria tritici blotch (STB) disease of wheat (Triticum aestivum L.), continuously threatens Ireland and Europe’s wheat crop causing loses up to 50% if left untreated. STB is mostly controlled by applying fungicides causing an economic loss of > €1bn annually to EU. Consequently, strains of Z. tritici have evolved fungicide resistance, which is impeding effective control. In addition, EU legislation has removed several fungicides due to environmental concerns, which is further driving resistance to the remaining chemistries within Z. tritici populations. Alternatively, genetic resistance is the most sustainable strategy; however, most commercial wheat varieties lack adequate STB resistance. Therefore, new breeding methodologies are needed to rapidly identify new sources of resistance to STB. Here we apply genomic selection (GS) and speed breeding (SB) technology to a 16-founder wheat multiparent advanced generation inter-cross (MAGIC) population (termed ‘NIAB Diverse MAGIC’), comprising of > 600 F7 inbred lines, to accelerate the identification of new sources of STB resistance. The MAGIC population has been genotyped with a 35K SNP array, with "1.2 million SNPs identified via founder exome capture and skim sequencing and imputation in the progeny currently in progress (NIAB, UCL). A subset of the NIAB Diverse MAGIC population encompassing maximum genetic diversity will be selected as a training population ("200 lines). The training population will be evaluated for STB resistance under SB to develop the prediction model using various algorithms (e.g. GBLUP, random forest, and Bayesian approaches), thus allowing to capture the variance of the large effect quantitative trait loci (QTL) together with the variance for the smaller effect QTL. The accuracy of predictions will be determined by correlating the genomic estimated breeding values (GEBVs) with the corrected phenotypes. GEBVs are then used to select candidates from the test population for advancement in the breeding cycle. The selected candidates will be subject to validation via SB and in the field at two sites in 2020 under high STB inoculum pressure. The accuracy of the models will be determined by correlating prediction accuracy via SB and the field. The genomic regions identified via genome-wide association studies will be aligned with previously reported QTL and catalogued resistance genes on the new bread wheat genome reference sequence (IWGSC RefSeq v1.0), allowing rapid identification of candidate genes conferring STB resistance. We envisage identifying new sources of resistance to STB disease that thereafter will be integrated into European wheat breeding programmes. 020261