WHEALBI aims to help the EU remain a major actor in world small grain cereal production while addressing the pressing global priorities of increasing and stabilizing primary production, improving food quality and safety, and reducing environmental impact.
WHEALBI will combine genomics, genetics and agronomy to improve European wheat and barley production in competitive and sustainable cropping systems. Germplasm representing the species diversity will be selected and characterized in unprecedented detail by next-generation-sequencing. Life history and adaptive traits will be evaluated in both transnational field experiments and a state-of-the-art precision phenotyping platform. Germplasm will be stored in a specialized and accessible bio-repository and associated data in knowledge bases that will represent a valuable legacy to the community. New methodologies will explore how to optimally exploit the large amount of new genotypic and phenotypic data available. They will focus on the design of ideotypes with improved yield stability and tolerance to biotic and climatic stresses and provide proof of concept of the efficiency of genome and phenome assisted selection. Ideotypes and reference varieties will be evaluated in innovative cropping systems, particularly organic farming and no-till agriculture, and an economic evaluation of these approaches will be conducted. The results will be disseminated to a broad user community, highlighting the benefits and issues associated with the adoption of what is considered sustainable and environmentally friendly wheat and barley crop production in a European context.
Whole genome association scans will be conducted for several traits, signatures of adaptive selection will be explored, and allele mining of candidate genes will reveal new variation associated with specific phenotypes. Pre-breeding tools and pipelines will be developed to optimize the efficiency of allele transfer from unadapted germplasm into elite breeding lines. New methodologies will explore how to optimally exploit the large amount of new genotypic and phenotypic data available. The particular output of WR will involve statistical methods and software and publications on translational genetics and breeding.