Abstract
With the development of high-throughput technologies, particularly for genomics and phenomics, biology has become a large-scale, data-rich field. High-throughput phenotyping (HTP) is an innovative technology that integrates advances in engineering or computer science into agriculture to optimize production while ensuring sustainability. In particular, the use of image-based HTP technologies allows us to collect a large number of phenotypes in an automated manner with less human labor and reduced costs, allowing us to efficiently evaluate phenotypes that were previously difficult to measure manually. The advent of HTP, coupled with the wealth of genomic data generated by next-generation sequencing technologies, provides new and exciting resources for studying complex traits. These new technologies also bring new challenges to quantitative genetics, namely the development of robust statistical frameworks that can accommodate spatial, temporal, heterogeneous, and high-dimensional phenotypic data. However, the impact of HTP-derived traits on genetic analysis in animal breeding and genetics has been limited. In this talk some real data examples of quantitative genetic modeling of image-derived traits will be presented.