Mapping the landscape of Varroa mite research: a bibliometric analysis of techniques and trends

This paper builds on our previous work by conducting a comprehensive bibliometric anal- ysis of Varroa mite research, addressing one of the most critical challenges in apiculture. Leveraging datasets and tools presented in our earlier conference paper, this study maps research trends, collab- oration networks, and technological advancements in Varroa mite management. Through an in-depth exploration of co-authorship patterns, keyword co-occurrence, and bibliographic coupling, the analysis uncovers the field's intellectual structure and collaborative landscape. Key findings highlight dominant themes such as chemical control methods, biological interventions, and the integration of advanced technologies like Artificial Intelligence (AI) and Internet of Things (IoT) for precise hive monitoring. The analysis also identifies emerging research regions and underrepresented countries, highlighting gaps in global collaboration and the need for a more inclusive research agenda. Furthermore, it underscores the ecological and economic urgency of combating Varroa infestations, especially in light of climate change, pollution, and habitat degradation. As a major conclusion, we propose the development of a new dataset with specific characteristics designed to enhance the detection and prediction of Varroa infestations. This dataset would support more precise monitoring through advanced Al models, en- abling proactive and sustainable control strategies. By offering a roadmap for integrating innovative technologies into apicultural practices, this study contributes to safeguarding pollinators, preserving biodiversity, and ensuring global food security.