Predicting Harvesting Crop Conditions to Prevent Pesticide Damage

Precision Agriculture

While pesticides protect crops, over-application can destroy a harvest. Predicting the outcome of a harvest season based on pesticide usage, soil data, and weather is a game-changer for precision agriculture.

Classification of Crop Health

I built an ensemble model integrating Linear Support Vector Classification and Stochastic Gradient Descent. The model accurately classified whether crops would survive, suffer pesticide damage, or fail due to other reasons.

Empowering Farmers

This real-world application provides farmers with actionable dosage recommendations, preventing toxic over-application, preserving soil health, and maximizing yield.