Fertilizer Recommendation Using Geospatial Technology: A Review
Main Article Content
Abstract
Fertilizer suggestion utilizing geospatial technology provides a dramatic shift from traditional blanket application methods to precise, site-specific nutrient management techniques. Farmers and researchers can use tools like Geographic Information Systems (GIS), Global Positioning Systems (GPS), and Remote Sensing (RS) to map soil fertility fluctuations, monitor crop health, and apply fertilizers precisely where and when they are needed. This method not only improves nutrient usage efficiency and waste reduction, but it also boosts crop productivity, often resulting in yield gains of 5-20% while cutting fertilizer inputs by 10- 30%. Furthermore, precise fertilization reduces environmental impacts including nutrient runoff and greenhouse gas emissions, resulting in more sustainable farming systems. Recent innovations, such as drones equipped with multispectral cameras, IoT-based soil sensors, and mobile decision support applications, are helping to bridge the gap between scientific data and on-farm operations, making precision agriculture more accessible to large-scale producers and smallholder’s a like In China, the integration of NDVI imaging with GPS-guided systems increased yields by up to 20% while drastically reducing nitrogen consumption. Similar measures in Ethiopia's EthioSIS project have resulted in significant yield increases, while variable rate technology in the United States Midwest has lowered input costs and reduced nitrate leaching. In the future, merging artificial intelligence, cloud computing, block chain, and crowdsourcing soil data promises to improve these systems accuracy and scalability. Together these advances enable farmers to make informed, data-driven decisions and assist governments in developing targeted subsidies and sustainability policies. Finally, geospatial fertilizer suggestion is more than a technological upgrade it is a conceptual shift toward smarter, more resilient, and environmentally responsible agriculture.