At the Bay Area Plant Hub meeting hosted by University of California, Berkeley, Li Mainhold, a PhD student from the Small Grains Crop Breeding Program presented new research on using artificial intelligence to improve crop breeding.

Li Meinhold is developing a prediction model using WheatCAP data from public wheat breeding programs. The model combines genomic data—about 500,000 DNA markers from ~8,400 wheat lines—with 40 environmental variables such as weather and location. 

We report new advances in improving resistance to stripe rust, a major disease affecting wheat production. Our study shows that combining adult-plant resistance genes, including Yr78 and Yr36, significantly enhances disease protection across diverse wheat backgrounds under field conditions. This work was conducted in collaboration with the teams of Dr. Jorge Dubcovsky and Dr.

We are excited to start a new project funded by USDA-NIFA to develop better wheat varieties for the future. In this project, we are testing new plant height genes (PLATZ1 and AP2L2) to replace the older ones (Rht-B1b, Rht-D1b) used since the Green Revolution. We will evaluate whether these new genes can help wheat grow better under tough conditions like drought, deep planting, and low nitrogen. Our goal is to develop varieties that produce high yields while staying resilient in changing environments.

At the UCD Small Grains Breeding Program, this week was about teamwork in action. We harvested field plots together –– students, staff, and researchers working side by side, learning by doing. It was hands-on, fast-paced, and a reminder that good agricultural science starts in the field.

The UC Davis Wheat Breeding Program continues its strong tradition of innovation in wheat genetics and breeding. Our team is developing wheat varieties for California producers using an integrated “package” approach that combines disease resistance, yield performance, grain quality, and nutritional traits. 

First Large‐Scale Breakdown of Yr15 Resistance to Wheat Yellow Rust (Puccinia striiformis f. sp. tritici) Recorded Globally.

How can agriculture directly improve public health? In collaboration with researchers from University of Nebraska–Lincoln, CIMMYT, Rothamsted Research, and multiple international partners, we contributed to a perspective proposing a new paradigm linking crop breeding, food systems, and health outcomes. The work highlights how improving dietary fiber levels in staple crops such as wheat could reduce risks of cardiovascular disease, type 2 diabetes, and colorectal cancer at the population scale.

Stripe rust remains one of the most destructive diseases affecting global wheat production. In collaboration with scientists the USDA-ARS Wheat Health, Genetics, and Quality Research Unit, our team introgressed the adult plant resistance gene Yr78 into durum wheat and evaluated its effect on stripe rust resistance. Field trials demonstrated that combining Yr78 with Yr36 significantly enhanced resistance, while additional stacking with seedling resistance genes Yr5 and Yr15 created a powerful multi-gene resistance package.

Whiteflies are major pests threatening cassava production worldwide. Collaborating with scientists from CIAT, ICARDA, and EMBL-EBI, weidentified quantitative trait loci controlling resistance to the whitefly Aleurotrachelus socialis. A major QTL on chromosome 8 explained over 35% of phenotypic variation, and associated SNP markers were validated across diverse cassava germplasm. These markers enable efficient marker-assisted selection of insect-resistant varieties.

Cassava mosaic disease (CMD) is one of the most devastating viral diseases affecting cassava production worldwide. In collaboration with researchers from the Japan International Research Center for Agricultural Sciences (JIRCAS), the Vietnamese Agricultural Genetics Institute, RIKEN Center for Sustainable Resource Science, and CIAT, we developed DNA markers targeting mutations associated with the CMD2 resistance locus. These markers enable efficient identification of resistant plants in breeding populations.