Digital Agriculture in Fruit Production

As the global population is projected to approach 10 billion by 2050, the resulting increase in food demand, combined with challenges such as climate change, water scarcity, and labor shortages, has made technology-driven approaches in agriculture indispensable. In fruit production, which is characterized by high labor intensity, this transformation is taking place within the framework of Agriculture 4.0 (Digital Agriculture), through the digitalization of production processes and the integration of Precision Agriculture practices based on the 5R principle with Internet of Things (IoT), artificial intelligence, and robotic systems. In fruit farming, digital technologies primarily focus on plant health monitoring, irrigation management, yield prediction, and autonomous harvesting. Image processing and deep learning–based algorithms (e.g., YOLO, Faster R-CNN) achieve accuracy levels exceeding 90% in fruit detection and disease classification, providing significant advantages for pre-harvest planning and yield forecasting. Furthermore, flower density and yield maps generated from unmanned aerial vehicle (UAV) data strengthen decision-support processes. Within the scope of precision agriculture, smart sprayers and early warning systems contribute to environmental and economic sustainability by reducing chemical inputs. However, technical challenges faced by autonomous robots under open-field conditions, high initial investment costs, and low levels of digital literacy remain the main barriers to widespread adoption. Digital transformation in fruit production is no longer an option but a strategic necessity for ensuring food security and competitiveness. The success of this process depends on the development of domestic technologies, the strengthening of digital infrastructure, and the enhancement of farmers’ digital competencies.