Beekeeping is a widespread economic activity in rural Tanzania, supporting over 2 million livelihoods. The country’s forests and woodlands, covering approximately 55% of its land area, provide habitat for an estimated 9.2 million honeybee colonies. This positions Tanzania as the second-largest honey producer in Africa and tenth globally. Absence of current information and effective policies hinders exploitation of the industry’s potential. This review presents scientific insights into Tanzania’s beekeeping sector, focusing on honeybee species, bee products, management practices, and conservation. Among three documented subspecies of Apis mellifera (Linnaeus, 1758), A. m. scutellata is the most widespread and commonly managed by indigenous beekeepers. Tanzania annually produces over 31,000 tonnes of honey and 1800 tonnes of beeswax, generating approximately USD 77.5 million and contributing about 1% to national GDP. The industry supports livelihoods, food security, and biodiversity conservation. Its sustained growth requires effective legal and administrative support, expanded scientific research, enhanced innovation, coordinated partnerships, and integrated nationwide initiatives.

Beekeeping is a widespread economic activity in rural Tanzania, supporting over 2 million livelihoods. The country's extensive forests and woodlands, covering approximately 55% of its land area, provide habitat and forage for an estimated 9.2 million honeybee colonies. This makes Tanzania the second-largest honey producer in Africa and the tenth-largest globally. Despite this potential, comprehensive and current information on the beekeeping industry remains scarce. This review synthesizes scientific insights into Tanzania's beekeeping sector, focusing on honeybee species, bee products, management practices, and conservation measures. Among the three documented subspecies of Apis mellifera (Linnaeus, 1758), A. m. scutellata is the most widespread and commonly managed by indigenous beekeepers. Tanzania annually produces over 31,000 tonnes of honey and 1800 tonnes of beeswax, generating approximately USD 77.5 million and contributing about 1% to the national GDP. The industry supports livelihoods, food security, biodiversity conservation, and international cooperation. However, its sustained growth requires strengthened legal and administrative frameworks, expanded scientific research, enhanced innovation, coordinated partnerships, and integrated nationwide initiatives.

Precision beekeeping is an emerging domain that utilizes digital technologies and tools, including sensors and artificial intelligence, to enhance the management and sustainability of apiaries. However, the lack of formalized and structured knowledge representation models hinders data integration, interoperability and decision support in the domain. This work presents a precision beekeeping ontology (PBO) designed to represent concepts related to bees, smart devices, monitoring and observation. The ontology was developed by adopting the seven-step methodology using Protégé. Domain understanding and determining the scope of the ontology were based on domain expert knowledge, literature review, standard vocabularies and upper ontologies (DUL, SSN/SOSA, AGROVOC and GEMET). Classes and class hierarchy, object and data properties were carefully defined to capture the concepts and relationships in the domain. Constraints on properties were specified and 74 instances were created based on a Kaggle beehive metrics dataset. 8 competence questions were predefined to determine the scope of knowledge, and later, 6 other related competence questions were defined and successfully executed based on internal hive temperature and hive weight by running SPARQL queries on the Apache Jena-Fuseki server. Domain expert validation and structural evaluation framework were applied and logical consistency was checked by HermiT reasoner in Protégé, using completeness, relevance, accuracy and clarity as evaluation criteria.