Global Food

A Global Food Ventures fellow is using plant DNA to better predict how plants will perform in a changing climate

Natural disasters driven by climate change are already commonplace, and the planet is projected to continue to get too hot, too dry, and too wet to sustain current food production. Farmers around the world are the first to be hit. Between 1991 and 2017, crop insurance losses increased by $27 billion in the United States alone. 

But Rafael Della Coletta, MnDRIVE Global Food Ventures Research Fellow and PhD candidate in the College of Food, Agricultural and Natural Resource Sciences (CFANS), is working to improve modeling systems that can predict which strains of maize will withstand yearly climatic changes, laying out a blueprint for plant breeders and ultimately, farmers. His work can’t come soon enough––the world’s population is projected to swell to more than 9 billion people during the next four decades, requiring a 70-percent increase in global food supply. 

“Climate change is changing the environments in which we grow food very quickly, but it takes a decade or so to release a new plant variety. Because the planet is changing quickly, we are worried that the production of new varieties cannot keep up with changes. We need to speed it up,” Della Coletta says. 

Using a vast database of maize DNA from around the world, computer models can already create genomic predictions that test which varieties or hybrids will do well under certain conditions. But current genomic prediction models don’t work very well, Della Coletta says.

“Especially when you want to make accurate predictions about what the performance of the plant will be in a specific region, such as Minnesota, Iowa, and Illinois. In my work, I’m digging into the maize genome to find unused genomic information that can help breeders predict with more accuracy,” he says.

He’s developed a more refined way to model a plant’s success, which seeks out specific genes that make certain varieties more resilient when faced with challenges such as drought and scorching heat. 

“Plant breeding is a numbers game, the more you can test, the more likely you’re going to find that rare, high-yielding variety that works across multiple environments,” says Candice Hirsch, PhD, an associate professor in the Department of Agronomy and Plant Genetics at CFANS, and Della Coletta’s advisor on the fellowship research. “He’s using more information so we don’t have to grow as many plants, which takes a lot of time and resources.”

Della Coletta’s research, which has received funding from the United States Department of Agriculture (USDA), focuses on maize in part due to the crop’s position as a global food staple, as well as the fact that humans have archived an immense amount of data on the plant’s genome. But his genomic prediction modeling can be applied to any plant species.  

Plant breeders will still plant the new varieties to test how they perform in real-world conditions, but predicting which combination of genes will likely result in the best plant for conditions reduces the amount of guess-and-check work that draws out the current plant breeding process. Della Coletta predicts that in the coming years, breeders will be able to create varieties that are suited for climatic changes on a yearly basis. 

“I think our last couple growing seasons have highlighted the challenges that producers are facing when trying to sustain our food system. Parts of the Midwest have been in an extreme drought for the majority of the growing season, while other parts have basically been underwater,” Hirsch says. “We’re constantly facing challenges, so we have to breed varieties that respond to those challenges. Rafa’s work is really at the crux of that.”