Daniel Robertson
University of Idaho, ID·Plant Science & Agriculture
Corn, wheat and sorghum supply most of the calories people eat, yet every year many of these plants break or topple before harvest. This failure, called lodging, destroys 5 to 25 percent of the potential harvest and costs farmers billions of dollars.
- Fields
Plant Science & Agriculture
Engineering
Computer Science
- Topics
stalk lodging
lodging resistance
corn
- Grants
- 1 known grant, through Jul 2030
What they work on
- Automate high-throughput phenotyping of cereal stalks, meaning fast trait measurements across many plants, to overcome the shortage of measured plants compared with millions of genetic markers.
- Find the cellular and subcellular features that drive stalk strength in crops such as corn, wheat and sorghum, so breeding can rest on engineering physics and biology.
- Develop multi-modal genomic foundation models, AI models that combine genome, imaging and metabolomic data, to pinpoint validated alleles linked to resistance to stalk lodging.
- Move harvest-integrated sensing, meaning sensors built into harvest equipment, toward field use, and turn results into a toolkit breeders can use.
More about the research
Breeders want sturdier varieties, but it is hard to link the plant's DNA to stalk strength. Plants carry millions of genetic markers, far more than the number of plants anyone can measure. This genome-to-phenome gap, the jump from genes to physical traits, slows the search for the genes that matter.
Why it matters
Lodging wastes 5 to 25 percent of potential cereal harvests and costs farmers billions of dollars each year. Tools that predict stalk strength from genes, together with sensors mounted on harvest equipment, could help breeders develop sturdier corn, wheat and sorghum. That could reduce crop losses, strengthen the food supply and support rural economies in the partner states.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Closest labs
Alexander Bucksch
University of Arizona, AZ·Plant Science & Agriculture·Early-career
Test whether one bean genotype forms several distinct root architecture types, each with its own plasticity curve across environments, by imaging roots grown under experimental conditions.
Lizhi Wang
George Mason University, VA·Engineering
Predict crop traits from genetic, management and environmental data by identifying a small subset of variables that interact as well as act additively, using machine learning and statistical selection methods.
Charles Anderson
Pennsylvania State University, PA·Plant Science & Agriculture
Test the "see-saw" hypothesis that grass guard cells swell while neighboring subsidiary cells deflate to open and close stomatal pores rapidly, using the model grass Brachypodium distachyon.
The school
University of Idaho: 8 labs on PI Pages, $140M a year on research, 71 research doctorates a year.
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