Research offers path to end world hunger within decade

The world's small-scale farmers now can see a path to solving global hunger over the next decade, with solutions—such as adopting climate-resilient crops through improving extension services—all culled rapidly via artificial intelligence from more than 500,000 scientific research articles.

The results are synthesized in 10 new research papers—authored by 77 scientists, researchers and librarians in 23 countries—as part of Ceres2030: Sustainable Solutions to End Hunger. The project is headquartered at Cornell University, with partners from the International Food Policy Research Institute (IFPRI) and the International Institute for Sustainable Development (IISD).

The papers were published concurrently on Oct. 12 in four journals—Nature Plants, Nature Sustainability, Nature Machine Intelligence and Nature Food—and assembled in a comprehensive package online: Sustainable Solutions to End Hunger.

Ceres2030 employed machine learning, librarian savvy and research synthesis methods to quickly scan a trove of thousands of scientific journals for ideas and websites from more than 60 agencies that can help eradicate world hunger.

"We're all bombarded with new research information and the question we must be asking is how do we make decisions from all of that information," said Ceres2030 principal investigator and co-director Jaron Porciello.

The United Nations' Sustainable Development Goal No. 2, known as SDG2, calls for ridding the world of hunger by 2030. Currently, more than 690 million people—about 8.9% of the world's population—are food-insecure, according to the United Nation's Food and Agriculture Organization (FAO). Due to the COVID-19 pandemic, that global statistic could easily rise by 10 million people a year from now, and by nearly 60 million people in five years.

"We're trying something new that hasn't been done before," Porciello said. "We know the tools weren't there, the methods weren't there and the teams weren't in place. Now, we've created some staircases to make science and world reality connect a little bit more. This approach could be replicated to build a scientific evidence base for many of the world's most complex policy problems"