Chandigarh University researchers use Artificial Intelligence to develop Model for predicting Accurate Crop Yield; Innovation to benefit Indian Farmers
Publish Date: 2026-06-27 07:08:00
Source Domain: www.tribuneindia.com
PRNewswire
Chandigarh [India], June 27: In a significant advancement for smart agriculture and precision farming, researchers at Chandigarh University have developed an Artificial Intelligence (AI)-powered Transformer Model that is capable of accurately predicting crop yields using satellite imagery, climate data and historical agricultural records.
– Researchers have leveraged Climate Data and Satellite Technology for developing the predictive model
The innovation would be instrumental in empowering farmers, policymakers and agricultural agencies to make informed decisions while strengthening food security and advancing resilient farm management.
The research, led by Kusum Lata, Assistant Professor Department of Computer Science Engineering, Chandigarh University, Dr Navneet Kaur Professor Department of CSE and Dr Simrandeep Singh Professor from University Centre of Research and Development at Chandigarh University that focuses on improving crop yield forecasting in Punjab’s agricultural heartland. The study, recently presented at the 2026 International Conference on Signal Processing and Electronics Design (ICSPED) at Chandigarh College of Engineering and Technology, Chandigarh that introduces a lightweight transformer-based system that leverages multi-source data to estimate crop production before harvest with greater accuracy and lower computational costs.
Notably, the accurate crop yield prediction has become increasingly important as farmers face growing challenges from climate variability, changing weather patterns and rising food demand. Traditional field surveys are often time-consuming, labour-intensive and limited in scale. The Chandigarh University researchers sought to overcome these limitations by integrating advanced AI techniques with real-time Earth observation data.
Kusum Lata, Assistant Professor Department of Computer Science Engineering at CU said, “The transformer model utilizes data from Sentinel-1 and Sentinel-2 satellites which are advanced…
