Speakers: Mao Li, PhD
Mao Li, PhD
Senior Research Scientist, Data Science Facility
Donald Danforth Plant Science Center
Mao Li is a mathematician who specializes in plant science. She is a Senior Research Scientist at Data Science Facility and a new PI at the Donald Danforth Plant Science Center. She got her PhD in biomathematics at Florida State University. Then she joined Topp Lab as a Postdoc Associate at the Danforth Center. Her research mainly focuses on quantitative data analysis, development of mathematical methods such as persistent homology based approaches, and computational algorithms to quantify plant morphology, below and above ground, from microbe to the globe.
Comprehensive 3D Imaging Analysis and Modeling for Inflorescence Architecture
Inflorescences are among the most intensely-studied structures in plant biology due to their importance in not only ecology and evolution, but also agriculture and crop production. However, they contain substantial morphological diversity and complexity, bringing challenges of comprehensive and precise quantification. Most features of inflorescence are not well-measured manually or with standard 2D imaging. Therefore, the combination of new technologies and computational tools is crucial for 3D in-depth phenotyping. In this talk, I will give an example of advanced 3D phenomics. We used X-ray computed tomography, developed custom computational pipelines, and advanced morphometrics to accurately and comprehensively phenotype grapevine inflorescence architecture with both general and organ-specific traits in a 3D framework. This 3D phenomics enable comprehensive characterization of complex architecture and can be broadly applied to root and shoot structures of many species.