In the absence of pollination, female reproductive organs, such as stigmas, senesce leading to an irrevocable loss in the reproductive potential of the flower. Thus, research to understand the dynamics of stigma survival in wheat could be key to achieving higher seed yields in hybrid seed production.

To advance our knowledge of stigma survival and senescence in wheat, we developed a high-throughput phenotyping approach using light microscopy, image analysis tools and machine learning techniques. We successfully implemented these approaches on field-grown male-sterile wheat cultivars to identify natural variation in the dynamics of stigma shape and size post-anthesis. We found (1) the presence of distinct stigma growth patterns among cultivars; (2) this trait to be robust across different environments and; (3) the existence of a common underlying developmental programme. This knowledge will equip researchers with a new framework to advance our mechanistic understanding of female fertility in wheat.