Abiotic Stress/Whole Plant Bio

Abstract

CS-4-4 - Computer vision and hyperspectral approaches to document temperature stress responses in maize seedlings

Sunday, July 15
2:03 PM - 2:23 PM

The yields of maize and other crops may be reduced substantially within the next century due to global climate change. Understanding how maize varieties respond to temperature extremes will be instrumental in developing varieties that can withstand future abiotic stresses while still maintaining high yield. A computer vision approach has been developed to enable the measurement of morphological traits and color in maize seedlings exposed to temperature stress. By monitoring these traits over time we can document a “phingerprint” of phenotypic responses to chilling or heat stress in diverse genotypes of maize enabling approaches to map the genomic basis for this variation. Hyperspectral data for maize seedlings exposed to temperature stress was also obtained in order to further probe the variability of responses in diverse genotypes and to provide early detection of stress responses prior to other manifestations. In addition to imaging-based phenotypes, we are investigating molecular responses to temperature extremes using both transcriptomic and phosphoproteomic methods. The combination of these diverse approaches will allow for a better understanding and characterization of the dynamics of responses of maize seedlings to temperature extremes. Integrating these data sets across genotypes and growth conditions will uncover the dynamics of maize responses to changing temperatures and allow for the discovery of genomic loci that could provide improved tolerance.


 

Co-Authors

Nathan Miller – University of Wisconsin; Susan St Dennis – University of Minnesota; Irina Makarevitch – Hamline University; Calli Anibas – University of Wisconsin; Natalia de Leon – University of Wisconsin; Edgar Spalding – University of Wisconsin; Nathan Springer – University of Minnesota; Cory Hirsch – University of Minnesota

Tara Enders, PhD

Postdoctoral associate
University of Minnesota

Postdoctoral associate in the lab of Nathan Springer at the University of Minnesota

Presentation(s):

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CS-4-4 - Computer vision and hyperspectral approaches to document temperature stress responses in maize seedlings



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