Drones equipped with multispectral or RGB sensors enable high-resolution monitoring of potato crops, identifying spatial variability in nutrient status through vegetation indices like NDVI. These indices help detect early signs of nutrient deficiencies, particularly nitrogen, phosphorus, and potassium. By integrating drone data into GIS-based prescription maps, farmers can apply variable-rate fertilization with greater accuracy. This targeted correction reduces input costs, optimizes nutrient uptake, and improves yield uniformity. The expected outcomes include enhanced nutrient use efficiency, lower risk of over-fertilization, and environmental benefits. For implementation, drone flights should be scheduled during key growth stages (canopy closure) and combined with calibrated field sampling to validate remote sensing data. Adoption is especially beneficial on medium to large farms with access to VRA equipment. This precision approach supports data-driven decision-making and improves the agronomic and economic performance of potato production.