What makes basil so good? Machine learning has been used to create basil plants that are extra-delicious. While we sadly cannot report firsthand on the herb's taste, the effort reflects a broader trend that involves using data science and machine learning to improve agriculture. The researchers behind the AI-optimized basil used machine learning to determine the growing conditions that would maximize the concentration of the volatile compounds responsible for basil's flavor. The study appears in the journal PLOS One today.
For Ferrero, OpenAg created what it calls a hazelnut computer--an indoor farm, made from structural steel and Styrofoam panels, that resembles a giant walk-in freezer. Inside, 16 hazelnut trees are maturing. LED lights simulate the sun, and every variable--air temperature, humidity, pH and carbon dioxide levels, water circulation--is controlled and optimized by artificial intelligence. Once OpenAg's algorithm determines the ideal hazelnut-growing recipe, Ferrero will compare it with climate and soil data from around the world as the company searches for a new place to farm. "We call it climate prospecting," says Caleb Harper, age 36, the founder and director of OpenAg.
As climate change makes it more difficult to grow crops in outdoor farms because of heat waves, more frequent storms, and more pests and disease, the researchers envision that climate-controlled, tech-filled greenhouses (which they call "food computers") could be an increasingly useful place to grow food. The technology could also eliminate food miles: Instead of shipping avocados from Mexico to China, a Chinese greenhouse could precisely recreate a Mexican climate in Beijing–or tweak it to create a climate even better for an avocado tree. "It definitely speeds up the timescale by which we can get interesting results," says Arielle Johnson, one of the researchers at MIT Media Lab Open Agriculture Initiative, or OpenAg. "When you talk to [Caleb Harper, the director of OpenAg], he's like, 'Yeah, basil is a fast-growing plant,' but in his terminology, fast-growing is six to eight weeks," says Babak Hodjat, CEO of Sentient, a company that also designs AI to help stock traders find patterns in the market and hospitals predict infections. "That's a long time to wait just to get a data point.
Absolutely, says Caleb Harper, director of the Open Agriculture Initiative at the MIT Media Lab. His team is using artificial intelligence to grow basil and other produce in enclosed climate-controlled environments, and, thanks to hundreds of sensors, crunching data to come up with "recipes" for growing the tastiest, most nutritious crops on the planet. Harper is not alone in using AI to revolutionize the future of food. Scientists, chefs, agronomists and techies are collecting vast catalogs of data around everything from food flavors and aromas to growing climates and plant biochemistry and creating algorithms for tastier, healthier, safer and more sustainable food. While chefs look at recipes for ingredients, artificial intelligence looks at the chemical composition of an ingredient to suggest combinations--creating new recipes based on the ingredient.
Scientists in the US have engineered tobacco plants that can grow up to 40% larger than normal in field trials. The researchers say they have found a way of overcoming natural restrictions in the process of photosynthesis that limit crop productivity. They believe the method could be used to significantly boost yields from important crops including rice and wheat. The study has been published in the journal Science. Researchers are growing increasingly concerned about the ability of the world to feed a growing population in a time of serious climate change.