Quad launches AI farm projects with $2.4mn investment

The US National Science Foundation (NSF) has announced the first awards under a Quad-backed initiative to use artificial intelligence (AI) to modernise agriculture across the United States of America and the Indo-Pacific.

The program, called Advancing Innovations for Empowering NextGen AGriculturE, or AI-ENGAGE, will support six international research projects, officials said on Thursday. The NSF is investing $2.4 million in the effort. The initiative is being carried out with partner agencies in Australia, India and Japan.

It brings together the NSF, Australia's Commonwealth Scientific and Industrial Research Organ-isation, the Japan Science and Technology Agency, and the Indian Council of Agricultural Re-search.

NSF described the effort as "a signature achievement of the Quad, demonstrating how the four nations' shared commitment to critical and emerging technologies research can transform agricul-ture to address pressing global challenges".

The projects will apply artificial intelligence and other emerging technologies to farming.

The goal is to help farmers increase crop yields, manage pests more effectively, and strengthen resilience.

"By integrating current and emerging technologies, like AI, into agriculture, we are advancing scientific frontiers to provide US farmers and their international counterparts with tools they need to increase crop yields, more effectively manage pests, strengthen agricultural resilience, and ensure a more secure food supply," said Brian Stone, performing the duties of NSF Director.

The six projects are spread across major US universities and involve researchers from at least three Quad countries.

Purdue University will develop autonomous aerial and ground robots for early disease detection in apple orchards.

Iowa State University will build "BRIDGE", an AI-based smartphone app and chatbot to help farmers identify and manage crop pests and diseases in real time.

Kansas State University will implement "Smart Scout", a computer vision system to estimate soybean yield and detect "lodging", or crops falling over.

Missouri University of Science and Technology and the University of Tennessee will develop the "HARVEST" system.