Reinforcing the transformative role of Artificial Intelligence in agriculture, researchers from VNR Vignana Jyothi Institute of Engineering & Technology (VNR VJIET), Hyderabad, have been granted an Indian patent for their AI-powered innovation, "Leaf Disease Detection System Using Convolutional Neural Networks." Developed by a multidisciplinary team of faculty members, the patented technology leverages deep learning to detect crop diseases at an early stage, enabling timely intervention, reducing crop losses, and supporting precision agriculture.
The innovation addresses one of agriculture's most persistent challenges, i.e., the delayed identification of plant diseases, which significantly impacts crop quality, yield, and farm productivity. Agriculture remains one of the largest contributors to India's economy and livelihoods, yet crop diseases continue to cause substantial losses every year. Traditionally, identifying diseases through manual inspection is labour-intensive, time-consuming, and often delayed until visible symptoms have spread across crops. VNR VJIET's patented system leverages Convolutional Neural Networks (CNNs) to analyse images of plant leaves, accurately identify diseases at an early stage, and recommend appropriate pesticide-based remedies. The system has demonstrated an accuracy of 97.7 per cent, enabling farmers to make informed decisions before diseases affect critical plant functions such as photosynthesis, pollination, and growth.
The patented innovation was developed through a collaborative effort between faculty members and researchers including Dr. Vijaya Saraswathi R, Dr. R. Vasavi, Dr. M. Gangappa, Laxmi Deepthi G, Dr. B. V. Seshu Kumari (IT), B. Ganesh Babu (EEE), Dr. A. Giri Prasad (EEE), K. Aruna Kumari (ECE), N. Sravani, and K. Jaya Jones.
Dr. Vijaya Saraswathi, Lead Researcher & Senior Assistant Professor, CSE Department, VNR VJIET remarked at the patent grant, "This innovation is deeply personal to me. Growing up in a farming family, I witnessed first-hand how crop diseases could wipe out an entire harvest simply because they were detected too late. That experience stayed with me and inspired us to explore how AI could bridge this gap for farmers. Our research focused on making the solution practical by recommending appropriate remedies. Receiving this patent is a recognition of years of collaborative research, and we hope this technology evolves into an accessible tool that empowers farmers and reduces crop losses."
