US, India Partner On AI-Powered Soybean Research Project

WASHINGTON, DC-A research project jointly backed by the US National Science Foundation (NSF) and India’s Ministry of Electronics and Information Technology (MeitY) has brought together universities and research institutions from both countries to develop advanced technologies for precision soybean breeding. As part of the collaboration, Dr. Xiaolei Huang, professor of computer science at the University of Memphis, has been awarded an NSF grant of $528,137 for the project.

The collaborative project brings together researchers from the University of Memphis, the University of Missouri, Kennesaw State University, the Indian Institute of Technology Delhi, Sher-e-Kashmir University of Agricultural Sciences and Technology of Kashmir, and the Indian Council of Agricultural Research’s National Soybean Research Institute.

US Congressman Steve Cohen of Tennessee announced the award on July 30. The project, titled “Collaborative Research: VINES: Track 1: NSF-MeitY: SoyWatch: Smart Sensing Network for Precision Soybean Breeding,” will begin on October 1 and run through September 30, 2029.

Announcing the award, Cohen praised the international partnership and its potential contribution to global food security.

“I congratulate Professor Huang for being awarded this prestigious National Science Foundation funding. His research efforts will improve soybean yields and productivity, which will help feed the ever-growing population of our planet. It is especially encouraging that this work is being done in collaboration with the government of India which pioneered ‘the green revolution’ in the 1960s and averted future famines,” the Congressman said.

The NSF said the project aims to develop a smart farming system that uses advanced sensing, NextG-enabled wireless communications and artificial intelligence to monitor, assess and improve soybean growth and performance.

The project seeks to address challenges faced by soybean farmers in both the United States and India, including pests, crop diseases and increasingly unpredictable weather. Researchers plan to develop a smart sensor network and AI-based analytical tools capable of monitoring crops and soil conditions in real time to support precision breeding and crop management.

The project has three main components: developing sensor arrays to measure soil nutrients, moisture and environmental conditions; designing energy-efficient wireless communication systems using drone-supported data collection and passive sensing technologies; and creating multimodal large language models that combine sensor data, drone imagery and environmental information to support crop phenotyping, pest management and yield forecasting.

According to the NSF, these technologies will be integrated into a single toolkit that generates data-driven agricultural insights for farmers and researchers. The project is also expected to strengthen scientific collaboration between the United States and India, support interdisciplinary research and student training, and contribute to the development of high-yielding, pest-resistant soybean varieties. (IANS)