Breeding of new cultivars is one of the most effective ways to respond quickly to the various impacts of climate change on crops, changes in lifestyles, and the needs of overseas markets. On the other hand, it is difficult to achieve these goals through the conventional breeding, because breeding requires time and labor. To improve the reproducibility and efficiency of the conventional breeding procedure, our group is conducting research to manage and utilize a large amount of data related to various breeding processes (Breeding Big Data). Specifically, by using high-precision environmental experiment chambers in addition to outdoor fields, we will 1) organize various types of omics information (genome, transcriptome, proteome, phenome and so on) obtained by high-throughput measuring hardware such as UAV and novel equipment, and 2) organize formats and ontologies for the various types of breeding information to manage breeding big data. Then, to apply these data to the breeding site, we will 3) develop breeding methods that combine breeding big data with super rapid generation scheme and marker selection technologies.
