Sugarcane Irrigation Dataset for SIDSS Framework

The dataset contains structured records of sugarcane crop parameters used for irrigation and yield prediction. It includes physiological features such as stomatal status, nitrogen, phosphorus, chlorophyll content, and leaf moisture variables, along with environmental factors like soil pH, soil humidity, microclimatic temperature, and wind speed. Additionally, it incorporates computed irrigation requirements (water liters per day) and predicted yield values generated using a CatBoost-based model. The dataset is designed to support machine learning-based decision-making for precision irrigation and crop yield estimation in sugarcane cultivation.