A new “super bean” developed with help from artificial intelligence could reach farmers within a few years, the result of University of Guelph research using AI to speed up the plant breeding process and increase productivity.
It’s thanks to BeanGPT, a platform designed to help producers uncover the best beans to grow in their local conditions.
BeanGPT is built on more than 314,000 scientific articles, along with archives of anecdotal observations and notes from more than 40 years of dry bean breeding research here at U of G.
“There was so much valuable information already here that we weren’t accessing,” explains Dr. Mohsen Yoosefzadeh Najafabadi, who leads the Dry Bean Breeding and Computational Biology Program in the Ontario Agricultural College. “It allowed us to develop an actual memory for the program.”
That memory has resulted in a robust hybrid AI platform that allows producers to input data on growing conditions, goals and disease. BeanGPT scans its extensive database to suggest the best crosses for a particular growing area. The result is a tailor-made dry bean customized for weather patterns, soil and a changing climate.
“We have field trials, genetic information, phenotyping, drone imaging, seed quality, weather and soil data right at our fingertips,” Yoosefzadeh Najafabadi says. “Using all this data, we can go from tens of thousands of suggested crosses to just a few hundred.”
The platform, already in use by Ontario Bean Growers, explains why each cross would be successful, allowing farmers to save years of development and acres of viable farmland.
“We have the power of history, current science and the future,” Yoosefzadeh Najafabadi says. “This is a revolutionary thing in plant breeding.”
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