Fruit crops are long-duration, high-value perennials whose nutrient requirement varies sharply across orchard blocks, tree age, canopy volume, and rootstock–scion combinations, making blanket, district-level recommended dose of fertilizer (RDF) prescriptions poorly suited to their management. Land Resource Inventory (LRI)  the systematic characterization of soil, terrain, drainage, climate, and land-use attributes at a defined spatial resolution  provides the foundational database on which scientifically defensible, site-specific fertilizer recommendation systems can be built. This review synthesizes the conceptual basis of LRI, the evolution of fertilizer recommendation approaches from blanket RDF to Soil Test Crop Response (STCR) targeted-yield equations, and their convergence with Geographic Information System (GIS), remote sensing, and land capability/suitability classification frameworks. It examines Site-Specific Nutrient Management (SSNM) and computer-based decision-support tools such as Nutrient Expert, reviews Indian and global case studies of GIS-based nutrient mapping in field and orchard situations, and discusses variable-rate and precision fertilization technologies emerging for fruit crops. Constraints  including the paucity of orchard-specific soil-test calibration data, spatial variability within single management zones, and the cost of dense grid sampling  are identified, along with future directions such as integration of hyperspectral/proximal sensing, machine-learning-based prescription models, and mobile-based farmer advisories. Adoption of LRI-based fertilizer recommendation systems can substantially improve nutrient use efficiency, orchard productivity, fruit quality, and environmental sustainability in comparison with conventional blanket dose approaches.