AI-BASED SOIL HEALTH ANALYSIS AND CROP RECOMMENDATION SYSTEM FOR SMART FERTILIZER MANAGEMENT IN PRECISION AGRICULTURE

Madhuri Deepak Mulje

doi:10.29121/ijoest.v10.i2.2026.749

Authors

Madhuri Deepak Mulje Assistant Professor, Prin Dr. Sudhakarrao Jadhavar Art Science and Commerce College, Narhe, India

DOI:

https://doi.org/10.29121/ijoest.v10.i2.2026.749

Keywords:

Artificial Intelligence, Precision Agriculture, Soil Health Analysis, Crop Recommendation, Smart Fertilizer Management, Machine Learning, Sustainable Farming, Nutrient Optimization, Agritech Systems

Abstract

Precision agriculture is changing the modern agriculture system by adopting the artificial intelligence (AI) technology that enhances the performance of agricultural systems and environmental conservation. The study introduces an artificial intelligence solution that assesses the state of soil and suggests farming methods to attain the most optimal use of fertilizers and enhanced crop production outcomes. The system employs machine learning algorithms to handle the key soil parameters that comprise pH, moisture levels, nutrient content and temperature readings. The system takes these inputs to decide the level of soil fertility as it also recommends the kind of crops and their particular requirements of fertilizer. The given model uses empirical data to pursue three goals that encompass the reduction of fertilizer use and minimization of environmental damage and the progress of more environmentally friendly practices in agriculture. The system will help farmers make prompt decisions as it will give them a smart system to communicate with. As demonstrated by the experiment, our system is superior when compared to the traditional methods, not only in terms of selecting crops precisely, but also with efficient nutrient management. The strategy will allow farmers to adopt clever farming practices that will offer them inexpensive and environmental-friendly practices that yield high agricultural yields.

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