MUMBAI, India, Sept. 22 -- Intellectual Property India has published a patent application (202611090951 A) filed by Dr. Rajani Vyas on July 27, 2026, for Method For Predicting Plant Disease Outbreaks Using Environmental Parameters.
Inventor includes Dr. Rajani Vyas.
The application for the patent was published on September 18, 2026, under issue no. 38/2026.
Abstract: The present invention discloses a method for predicting plant disease outbreaks using environmental parameters to facilitate early disease detection and improve agricultural decision-making. The method comprises acquiring real-time environmental data from multiple sensing sources, including temperature, relative humidity, soil moisture, rainfall, leaf wetness, wind speed, solar radiation, and atmospheric pressure sensors. The collected data is pre-processed by removing noise, handling missing values, eliminating duplicate records, validating sensor measurements, and normalizing environmental variables to ensure data reliability. The processed data is subjected to feature extraction to identify significant environmental factors associated with disease development. A predictive analytics module employing one or more machine learning algorithms analyses the extracted features together with historical environmental observations to estimate the probability of plant disease occurrence. The predicted results are classified into predefined disease risk levels comprising low, moderate, high, and critical risk. Based on the identified risk level, an automated alert module generates early warning notifications and preventive recommendations for farmers through mobile applications, web-based platforms, or Internet of Things (IoT)-enabled communication systems. The method continuously updates the predictive model using newly acquired environmental observations, thereby improving prediction accuracy under changing climatic conditions and different agricultural environments. The invention enables timely preventive interventions, reduces crop losses, optimizes pesticide usage, minimizes production costs, and enhances sustainable farming practices. The proposed method is applicable to diverse crop varieties, greenhouse cultivation, open-field agriculture, and precision farming systems, providing an intelligent, adaptive, and scalable solution for environmental parameter- based plant disease outbreak prediction.
Disclaimer: Curated by HT Syndication.
