TY - JA AU - Zelba,O. AU - Wilderspin,S. AU - Hubbard,A. AU - Nellist,C.F. AU - Mortensen,A.K. AU - Schulz,P. AU - Huerta-Espino,J. AU - Singh,R.P. AU - Sorensen,C.K. TI - The adult plant resistance (APR) genes Yr18, Yr29 and Yr46 in spring wheat showed significant effect against important yellow rust races under North-West European field conditions SN - 0014-2336 PY - 2024/// CY - Dordrecht (Netherlands) PB - Springer Netherlands, KW - Spring wheat KW - AGROVOC KW - Breeding KW - Phenotyping KW - Puccinia striiformis KW - Learning KW - Yields KW - Rusts KW - Europe N1 - Peer review; Open Access N2 - Yellow rust caused by Puccinia striiformis f. sp. tritici (Pst) is one of the most important wheat diseases. Adult plant resistance (APR) genes have gained the attention of breeders and scientists because they show higher durability compared to major race-specific genes. Here, we determined the effect of the APR genes Yr18, Yr29 and Yr46 in North-West European field conditions against three currently important Pst races. We used three pairs of sibling wheat lines developed at CIMMYT, which consisted of a line with the functional resistance gene and a sibling with its non-functional allele. All APR genes showed significant effects against the Pst races Warrior and Warrior (-), and a race of the highly aggressive strain PstS2. The effects of Yr18 and Yr46 were especially substantial in slowing down disease progress. This effect was apparent in both Denmark, where susceptible controls reached 100 percent disease severity, and in United Kingdom where disease pressure was lower. We further validated field results by quantifying fungal biomass in leaf samples and by micro-phenotyping of samples collected during early disease development. Microscopic image analyses using deep learning allowed us to quantify separately the APR effects on leaf colonization and pustule formation. Our results show that the three APR genes can be used in breeding yellow rust resistant varieties of spring wheat to be grown in North-West European conditions, and that deep learning image analysis can be an effective method to quantify effects of APR on colonisation and pustule formation UR - https://hdl.handle.net/10883/34605 DO - https://doi.org/10.1007/s10681-024-03355-w T2 - Euphytica ER -