Analyzing and Forecasting Soil PH Prediction

In short, measurement of soil pH has importance in terms of health and productivity besides sustainability in farm practices. Soil pH prediction up to a very accurate degree therefore would hold value not only for soil management but also for better fertilizer application. The paper reports on the data-driven approach that can predict soil pH using machine learning algorithms. It has to do with the environmental factors supplemented with geospatial data from historical records from the soil, and it is highly accurate in predicting pH levels involved. Methodology: The process includes data preprocessing, feature selection, and training using models algorithms such as Random Forest and Gradient Boosting. Outputs of this study authenticate truthfulness presented in the built model since.