The Agri-IQ Revolution: Crop and Fertilizer Recommendations Tailored by Nature

Agriculture is increasingly challenged by soil nutrient depletion, climate variability, and resource inefficiency. Advanced technologies have to be incorporated into agriculture and this makes the present assessment of the possible revolution the AI and ML in developing the crop and fertilizer recommendation systems relevant. Drawing from global research and case studies, multiple methodologies are combined including the neural network, a decision tree, as well as complex ensemble models of Random Forest and XGBoost, which can determine the optimality of soil nutrient management and crop selection, while simultaneously ensuring balance between environmental sustainability and economic productivity through tailored recommendations based on soil properties that are detailed on nitrogen (N), phosphorus (P), potassium (K), and pH levels. Some of the existing gaps in pre-existing research, like limited adaptability to localized agricultural conditions, open avenues for future interdisciplinary innovations. Reviewing the book underlines how AI-driven insights can change traditional farming practices toward enabling sustainable agricultural systems that harmonize with the dynamics of nature.