MUMBAI, India, Jan. 9 -- Intellectual Property India has published a patent application (202511116282 A) filed by Rahul Palaria; Dr. Ashish Bhushan Khare; Dr. Hitender Singh Jalal; Mamta Joshi; Deep Chanda Andola; Harendra Pratap Singh; and Rohan Gupta, Nainital, Uttarakhand, on Nov. 24, 2025, for 'system and method for enhanced crop yield prediction using an adaptive hybrid dssat.'
Inventor(s) include Rahul Palaria; Dr. Ashish Bhushan Khare; Dr. Hitender Singh Jalal; Mamta Joshi; Deep Chanda Andola; Harendra Pratap Singh; and Rohan Gupta.
The application for the patent was published on Jan. 9, under issue no. 02/2026.
According to the abstract released by the Intellectual Property India: "The present invention relates to a system and method for predicting crop yield using an adaptive hybrid modelling framework that integrates DSSAT-generated agro-climatic, soil, and crop-management datasets with an optimized Random Forest machine learning engine. The system preprocesses multidomain simulation data through domain-aware normalization, mechanistic feature engineering, and noise reduction, followed by a dynamic feature-interaction analysis that models nonlinear and conditional dependencies unique to DSSAT variables. A customized Random Forest model is trained on historical DSSAT outputs and ground-truth yield records, and an adaptive calibration module adjusts model behaviour using cross-season residual patterns to mitigate simulation bias and climatic variability. A prediction engine processes new-season DSSAT datasets to generate yield forecasts accompanied by interpretability outputs tailored to crop-growth semantics. The invention delivers enhanced accuracy, stability, and transparency in yield estimation, enabling deployment in agricultural advisory systems, crop-insurance modelling, and regional food-security planning."
Disclaimer: Curated by HT Syndication.
