- Extreme weather associated with climate change will affect food security
- Scientists are building virtual plant models for staple food crops
- Models could predict plant varieties that increase yield under adverse climate conditions
Spicy sesame noodles. A juicy BLT. Lobster rolls. Fish tacos on soft corn tortillas. Gooey, finger-staining blueberry pie. These are just a few of the delights of the summer eating season.
In a year when it seems like just about everything has been canceled, cooking and eating well is keeping many of us going. But what if food is just one more thing we can no longer count on?
It’s not just fragile supply chains that we need to worry about, but climate change. Severe heat, water scarcity, wildfires, and destructive storms are increasingly disrupting agricultural productivity.
“We’re all experiencing the extreme weather that’s associated with climate change,” says Amy Marshall-Colón, a plant biologist at the University of Illinois. “There’s no doubt that it’s going to impact our food supply.”
That sounds bad, but before you panic, know that there may be a solution. Marshall-Colón is the director of a global scientific collaboration aimed at building virtual plants. Known as Crops in silico, the project will model soybeans, corn, wheat, and sorghum—the source of sixty percent of our food .
“My dream is that this is a tool that will improve food security,” says Marshall-Colón. “If we have a really good model of a crop that we know is doing a good job of simulating response to current conditions, then we can do a good job of predicting crop response to future untested scenarios.”
Yggdrasil connects the worlds
Modeling plants is nothing new. But most existing models focus tightly on only one aspect of the plant. The goal of Crops in silico is to stitch those models together into an entire virtual plant for each of the target crops.
“You could have a model that’s only about the roots. Or a model entirely focused on photosynthesis in leaves,” says Marshall-Colón. “But we don’t yet have a single crop model that captures a whole plant and all of the dynamics.”
To make matters worse, many of these partial plant models have been written in different computational languages. And they run on different time scales because they’re modeling different aspects of the plant.
But Meagan Lang, a research scientist at the National Center for Supercomputing Applications (NCSA), has developed a solution for that. She’s built a computational framework called yggdrasil, after the Norse tree that connects all of the worlds.
Yggdrasil takes advantage of APIs for the languages in which the original models have been written and performs a translation that allows outputs from one model to be passed as inputs to the next.
“The project is a really tight collaboration between biologists and computer scientists,” says Marshall-Colón. “Biologists have the models of the plants, and the computer scientists are figuring out how to computationally pass the information between these models.”
Putting the puzzle pieces together
Two years into this four-year project, Crops in silico has made the greatest progress with modeling soybeans. One reason for that is because the SoyFACE facility, the National Soybean Research Laboratory, and the USDA Soybean Germplasm Collection are located at the University of Illinois. Some of the world’s leading experts on soybeans have been collecting extensive information about soy crops for years, providing the project with rich data to draw upon.
“The biggest limitation for this project or any modeling project is what data is available for you to build models and what data’s available for you to test models,” says Marshall-Colón.
The Australian Wheat Hub provides similar expertise and data for wheat. Farmers in Australia have been growing wheat in a hot, dry environment for decades—exactly the conditions other regions may soon be facing due to climate change.
Marshall-Colón hopes that in later stages, Crops in silico will be able to predict things like whether turning up certain biochemical pathways in wheat will increase yield in a hot dry environment. Then the Australian partners will grow that variety, literally in the field, to see if the prediction is correct.
“We’re still in the building phase, still putting the puzzle pieces together,” says Marshall-Colón. “But at the end of this project we hope to have very specific predictions that we can actually test and see if we are right.”
The team’s current efforts focus on the staple crops that provide most of the world’s nutrition. But integrated virtual whole plant models could improve the outlook for all kinds of food, not just the bare necessities.
“My goal is that in the future we could do this for other things we like to eat. For the really delicious things that are very high risk. All of the things that everybody loves: bananas, coffee, chocolate,” says Marshall-Colón. “We have a beautiful, delicious variety of food that's available to us. I hate thinking that someday we might not have access to it.”
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