### Literature Review on Digital Twins  
Digital representations/shadows of physical entities enabled by smart analytics and data have synchronized various sectors, including agriculture [18]. These DTs serve as virtual replicas of physical objects, processes, or systems, allowing real-time monitoring and simulation to enhance productivity and efficiency [19; 20]. More specifically, in the domain of agriculture, DTs can enable farmers to use digital tools that represent real-time augmented and monitored physical agricultural product life cycles. Figure 1: Flowchart of the study’s framework, illustrating the hypotheses, research methods, stakeholder engagement, data analysis, key findings, and conclusions. Woody crops are a specific branch of agriculture that includes perennial plants like vines, fruit trees (such as almond or peach trees), and shrubs (such as cranberries). These crops require long-term management strategies due to their extended growth cycles and high initial investment. They take years to mature, with significant maintenance costs, specific soil and climate needs, and complex pest management [21; 22; 23; 24]. Their cultivation is labor-intensive, with mixed environmental impacts and economic risks due to market fluctuations [25; 26; 27]. Harvesting and post-harvest handling require specialized techniques to maintain quality and extend product shelf life [28]. Therefore, considering the unique characteristics of such crops, education, and training can be more challenging than in other types of agriculture. Mastering education in woody crops demands more dedication, time, and effort compared to other agricultural fields. To this end, DTs can potentially integrate expert knowledge from different stakeholders [29], and their inclusion in education can significantly enhance the learning experience. DTs could simulate the complete cycle of a woody crop within a short period, allowing students to observe and understand the growth stages, disease progression, and environmental impacts without the need for a year-long field study. For example, in viticulture, DTs can simulate various pruning techniques or pest management strategies [30], helping students visualize and analyze the most effective approaches. By integrating real-time data from IoT (Internet of Things) sensors and UAVs (Unmanned Aerial Vehicles) [31] and search algorithms, such as tree-based structures, hashing techniques, or indexed databases [32], DTs can provide a dynamic and interactive educational tool that enables students to make informed decisions and understand the impact of different farming practices. Advanced predictive models within DTs can also forecast yield, offering students insights into market planning and resource allocation. In summary, using DTs in education for woody crop management can increase learning efficiency, reduce the need for extensive fieldwork, and promote sustainable agricultural practices. Furthermore, DTs allow for the precise tracking of growth stages, pest infestations, and other critical factors affecting the health and yield of the crops. In addition, DTs can integrate various data sources such as satellite imagery, sensor data, and historical weather patterns to predict and mitigate potential issues before they affect the crops. The gamification and digitization of the production chain can have promising results in various environmental targets for resource optimization or other cost-saving activities within the boundaries of sustainable agriculture [33]. The visualization from imagery data sourcing from various sources (soil, plant conditions, weather data, UAV, etc.) empowers them with well-informed decision-making in many vital processes (irrigation, pest management, and eco fertilization). Farmers can make data-driven decisions that enhance productivity while minimizing environmental impact by providing a comprehensive view of the vineyard.