Precision Agriculture in Sugarcane Farming: A PRISMA-Based Systematic Review of Technologies, Adoption Gaps, and Sustainability Pathways

Sugarcane industry faces challenges from resource depletion, environmental degradation, and inefficient management. Precision agriculture (PA) offers a transformative solution through digital, geospatial, and automation technologies. This PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) - based systematic review, critically evaluates the evolution, adoption, and sustainability implications of the PA in sugarcane farming. Key technologies such as laser land leveling, global navigation satellite systems, variable rate technology, hyperspectral imaging, unmanned aerial vehicles, internet of things, and machine learning improve yield prediction, soil health, water-use efficiency, and carbon footprint reduction. However, large-scale adoption of such technologies is limited due to their high costs, poor data integration, and limited farmer training. This study recommends policy support through subsidies, shared equipment hubs, and open-access digital platforms while suggesting capacity-building initiatives and public-private partnerships for technology diffusion among smallholders. Future studies should prioritize field validation, techno-economic evaluation, and life-cycle assessments. Integrating artificial intelligence-driven systems with circular bio-economy models will boost resilience and sustainability. This review outlines a pathway toward precision-driven, low-carbon sugarcane production.