## 4 Discussion  
This research set out to investigate how integrating Digital Twins (DTs) with AI-driven personal assistants and immersive XR environments can enhance educational outcomes and decision-making for woody crops. By leveraging real-time data, predictive models, and interactive learning experiences, we aimed to address the limitations of traditional agriculture training methods, which often require significant time, resources,  
Figure 8: Virtualized environment of (**a**) olive trees, (**b**) banana plantation, (**c**) mango orchard, and (**d**) cannabis field. and specialized expertise. In doing so, our work goes beyond the prior literature that predominantly focuses on monitoring and data collection, emphasizing instead experiential learning, scalability, and user engagement. Most of the existing research on Digital Twins in agriculture centers on real-time monitoring or data-driven decision-making for annual crops or simpler production scenarios [29, 30, 63]. Few studies, however, delve into merging DTs with immersive XR and AI-driven personal assistants specifically for woody crops, which present unique challenges due to their longer growth cycles, complex pest management needs, and higher resource demands [24, 27]. By introducing a framework that integrates real-time data from DTs with AI-enabled NPC educators in a serious-gaming context, this paper offers a new dimension to both domains. From the DT perspective, our approach demonstrates how digital replicas of vineyards or orchards can evolve into highly interactive learning tools, transcending remote sensing or static data visualization. Instead, we provide hands-on practice in simulated environments, where users can test management strategies or pest-control methods in a virtual \"sandbox\", receiving immediate feedback on possible long-term outcomes through DT-based analytics and AI models. From the woody crops perspective, our work addresses the challenge of educating stakeholders in complex, perennial agricultural systems--an aspect often overlooked due to the high cost and extensive timelines required for real-world orchard or vineyard trials [41, 42]. It is crucial to highlight the environmental and sustainability benefits the synergy between integrating immersive technologies and AI in viticulture can offer. The ability to simulate and predict the outcomes of various farming practices in a virtual environment means that resource-intensive experiments can be conducted without the actual consumption of water, fertilizers, or pesticides. This minimizes the environmental footprint and allows for the exploration of more sustainable farming practices. By leveraging DTs and AI, farmers and researchers can identify optimal strategies for water management, pest control, and crop rotation that reduce the reliance on chemical inputs and enhance soil health, contributing to the broader goals of environmental sustainability and climate resilience in agriculture. Furthermore, adopting these technologies in viticulture education and training programs promotes a forward-thinking mindset among the next generation of farmers and viticulturists. As they become accustomed to using digital tools and data-driven insights for decision-making, they are more likely to implement sustainable and innovative practices in their operations. This shift towards a more informed and technologically savvy agricultural workforce is essential for addressing the challenges posed by climate change and global food security. The immersive learning experiences provided by DTs and AI make agricultural education more engaging and effective and ensure that future farmers are well-equipped to adopt productive and sustainable practices, securing the future of viticulture and agriculture for generations to come. This follows the principles of bounded rationality in AI, where systems must operate optimally within the constraints of computational resources and environmental complexity [8].