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@article{187749,
        author = {R. Sugunthakunthalambigai and R.Brimapureeswaran and M. Radha},
        title = {Mathematical and AI-Driven Dynamic Modeling of Biochar–Soil Interactions for Sustainable Fertility Optimization},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {6},
        pages = {6661-6667},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=187749},
        abstract = {This study presents an advanced AI-enhanced dynamic modeling framework for predicting and optimizing biochar–soil interactions through coupled soil process equations, numerical simulation, and data-driven optimization. The improved model captures nonlinear relationships among nitrogen cycling, microbial proliferation, carbon stabilization, and water retention. By integrating differential equation systems with machine-learning optimization, the study identifies optimal biochar application levels that enhance long-term soil fertility and sustainability. Results demonstrate that moderate biochar rates significantly improve nutrient efficiency, microbial activity, carbon persistence, and soil moisture behaviour. The refined framework provides a powerful decision-support system for precision biochar management.},
        keywords = {Biochar, Soil Fertility, Artificial Intelligence, Nitrogen Dynamics, Soil Organic Carbon, Microbial Activity, Water Retention},
        month = {November},
        }