TY - JA AU - Fradgley,N.S. AU - Bacon,J. AU - Bentley,A.R. AU - Costa-Neto,G. AU - Cottrell,A. AU - Crossa,J. AU - Cuevas,J. AU - Kerton,M. AU - Pope,E. AU - Swarbreck,S.M. AU - Gardner,K.A. TI - Prediction of near-term climate change impacts on UK wheat quality and the potential for adaptation through plant breeding SN - 1354-1013 PY - 2023/// CY - United Kingdom PB - Wiley, KW - Adaptation KW - AGROVOC KW - Climate change KW - Grain KW - Quality KW - Wheat KW - Breeding KW - United Kingdom of Great Britain and Northern Ireland N1 - Peer review; Open Access N2 - Wheat is a major crop worldwide, mainly cultivated for human consumption and animal feed. Grain quality is paramount in determining its value and downstream use. While we know that climate change threatens global crop yields, a better understanding of impacts on wheat end-use quality is also critical. Combining quantitative genetics with climate model outputs, we investigated UK-wide trends in genotypic adaptation for wheat quality traits. In our approach, we augmented genomic prediction models with environmental characterisation of field trials to predict trait values and climate effects in historical field trial data between 2001 and 2020. Addition of environmental covariates, such as temperature and rainfall, successfully enabled prediction of genotype by environment interactions (G × E), and increased prediction accuracy of most traits for new genotypes in new year cross validation. We then extended predictions from these models to much larger numbers of simulated environments using climate scenarios projected under Representative Concentration Pathways 8.5 for 2050–2069. We found geographically varying climate change impacts on wheat quality due to contrasting associations between specific weather covariables and quality traits across the UK. Notably, negative impacts on quality traits were predicted in the East of the UK due to increased summer temperatures while the climate in the North and South-west may become more favourable with increased summer temperatures. Furthermore, by projecting 167,040 simulated future genotype–environment combinations, we found only limited potential for breeding to exploit predictable G × E to mitigate year-to-year environmental variability for most traits except Hagberg falling number. This suggests low adaptability of current UK wheat germplasm across future UK climates. More generally, approaches demonstrated here will be critical to enable adaptation of global crops to near-term climate change UR - https://hdl.handle.net/10883/22384 DO - https://doi.org/10.1111/gcb.16552 T2 - Global Change Biology ER -