Associate Professor Cory Hirsch

This group is working on two projects that use MSI resources:

• Understanding abiotic stress: Abiotic stress, such as extreme temperatures, severely limits agricultural productivity. Many approaches to understanding stress response miss the important connectedness of complex biological functions. The primary goal of this project is to extend our understanding of abiotic stress response dynamics by integrating high-information phenotyping, ionomics (elemental profiles), and transcriptomics data together together. This project has three main objectives:
  • Determine the heritability of hyperspectral signatures and morphological traits under related stress environments to test if these phenotypic traits are indeed heritable as would be necessary for breeding purposes
  • Integrate high-information phenotyping, ionomics, and global gene expression data to understand physiological, morphological, elemental, and transcriptomic response of stress across seedling development holistically
  • Develop and test predictive models for stress response from kernel to seedling
• Genomics of different types of plant pathogens: This includes conducting multiple genome assemblies, resequencing  pathogen populations, and population level analyses. The main objective of this research is to identify genomic regions associated with increased pathogen pressures on crops. 

MSI is used for all NGS data analysis and other downstream computationally intensive task and to computationally analyze thousands of generated images, both RGB and hyperspectral.

This research was featured on the MSI website in:

• December 2019: Discovering the Origins of a Wheat Stem Rust Lineage
• September 2018: Genomic Studies of Oat Crown Rust