Postharvest losses of pear and apple fruit quality are costly to the tree fruit industry. Despite layers of sophisticated postharvest technology, there are no current reliable risk assessment tools for losses of fruit quality during the postharvest period. Furthermore, production practices, the orchard environment, postharvest practices, and cultivar differences all play a coordinated role to specify fruit quality in the postharvest period - how these factors all interact is poorly understood. Our goal is to find genetic factors related to postharvest fruit quality traits. This involves experimentally isolating genetic factors that play a role in important postharvest fruit quality traits. Currently, we are focused on searching for genetic factors that are related to the risk for postharvest losses in quality. Identification of these factors will allow us to better understand the molecular mechanisms that influence postharvest quality, giving us insight that could lead to enhanced management practices. This includes more precise application of existing technology, and the development of new technology to enhance postharvest fruit quality. Our past work has shown that gene activity signatures are relatable to aspects of fruit physiology in the postharvest period. A significant hurdle to discovering key important genetic factors is the complex nature of postharvest fruit quality traits - large numbers of genes with complex patterns of expression and co-expression play a role. This challenge is compounded by the complex evolutionary and domestication history of Amygdaloideae (apples and pears). Therefore, this project aims to develop cultivar-specific genome resources (for each cultivar of interest) to enable higher fidelity gene expression measurements and also allow comparative genome analyses to search for genetic factors that underpin important postharvest traits. These new genomes will help us navigate the complex genome landscape of apples and pears. Objectives: 1. Generate quantitative gene activity measurements of important pear and apple cultivars. 2. Assemble and annotate genomes of important pear and apple cultivars. 3. Cross reference gene activity datasets with new genomes to search for genomic loci that are relatable to postharvest pear and apple traits.