Nutrigrow Using Gradient Boosting Regressor

In modern agriculture, the quest for enhanced crop yield and nutrient efficiency is paramount. Leveraging the Gradient Boosting Regressor algorithm, this research proposes a novel method to address this challenge. By analyzing historical rainfall data and soil fertility levels, the system predicts crop nutrient requirements, aiding farmers in making informed decisions on fertilizer application. Moreover, real-time weather forecasts are integrated to issue timely alerts, mitigating risks associated with adverse weather conditions. This holistic approach not only enhances crop yields but also minimizes nutrient wastage, contributing to environmental sustainability and economic viability. Through the synergy of advanced algorithms and agricultural data, this work offers a promising avenue for optimizing crop production and resource management in modern farming practices.