MIT researchers use machine learning to grow better basil

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Spotted: Researchers from MIT are growing better basil, with no help from genetic modification. Instead, they used machine learning to determine optimum growing conditions (24-hour exposure to light helps). The plants were grown in modified shipping containers. The environmental factors – like temperature, light, humidity – were controlled automatically. The study’s findings were published earlier this month.

“We were trying to use the machine learning to learn how to change the climate,” Caleb Harper, principal research scientist at MIT’s Media Lab, told the Boston Globe. “Could it look through all these variables and come up with alternative recipes that would change the climate to express more of what we wanted?“

The team will use the data from the basil project to study how to improve plants’ ability to fight diseases. The data will also be used to study how plants could respond to climate change.

Takeaway: In addition to bringing the world tastier pesto, this research – known as cyber agriculture — could help farmers and the food industry prepare for climate change. The MIT team is already working on a study on hazelnut trees for Italian candy manufacturer Ferrero. “When you grow things in a field, you have to rely on the weather and other factors to cooperate, and you have to wait for the next growing season,” MIT’s John de la Parra said. “With systems like ours, we can vastly increase the amount of knowledge that can be gained much more quickly.” Studies show that artificial intelligence and machine learning are poised to play an increased role in agriculture. Springwise has recently spotted other innovations that use technology to improve agriculture, including a commercial unit that uses machine learning to provide ideal growing conditions for plants and a robot that can pollinate plants.

Website: www.media.mit.edu
Contact: www.media.mit.edu/contact

Published in: April

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