MUMBAI, India, March 13 -- Intellectual Property India has published a patent application (202641003401 A) filed by Sri Sairam Institute Of Technology; G. Valarmathi; K. Sivasankari; G. Saravanan; P. Keertana; G. Swetha; and K. R. Abirami Devi, Chennai, Tamil Nadu, on Jan. 13, for 'automated classification of nutrient deficiencies in paddy using deep learning.'
Inventor(s) include G. Valarmathi; K. Sivasankari; G. Saravanan; P. Keertana; G. Swetha; and K. R. Abirami Devi.
The application for the patent was published on March 13, under issue no. 11/2026.
According to the abstract released by the Intellectual Property India: "Nutrient deficiencies in rice plants can severely impact growth and yield, posing significant challenges to agricultural productivity. Current techniques for spotting these flaws frequently depend on labour-intensive, error-prone manual examination. This work proposes an automated solution using deep learnil)g techniques to accurately classify nutrient deficiencies in rice plants. The methodology involves preprocessing rice plant images through resizing and augmentation, followed by training a fine-tuned ResNet50 model to extract deep features specific to nutrient deficiencies. The system's performance is assessed using metrics such as accuracy, precision, sensitivity, and Fl-score. By leveraging advanced image processing and neural networks, this approach aims to provide a more efficient and reliable means of identifying nutrient deficiencies, thereby supporting better crop management and productivity."
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