Advances in animal traceability systems: A systematic review of technologies, benefits, and challenges

It is a common course that many families’ livelihoods in Sub-Saharan Africa are most importantly dependent on agriculture, especially livestock. To that end, it is estimated that the worldwide population of cattle is around 1.3 billion. However, animal disease outbreaks have caused many problems for economies, livelihoods, and communities. Therefore, this prevalent danger from livestock infectious diseases would cripple economies, not to mention that it would destabilize food security for affected communities. Given the impact of such outbreaks, measures must therefore be put in place to manage cattle activities to ensure the best profits and safety measures of livestock are reached. Animal traceability technologies have been introduced as measures for some of the livestock problems identified. A systematic literature review of animal traceability technologies is conducted following the process: 1) Planning by formulating research questions, 2) Article selection process from databases such as Science Direct and IEEE between 2006 and 2025, 3) Meta-analysis and data extraction of the 50 selected articles 4) Write-up of the results. A novel classification framework for animal traceability technologies is developed that goes beyond traditional technology-centric reviews. The integrated conceptual framework categorises traceability innovations across four complementary dimensions: systems, frameworks, benefits, and challenges. From the results, the commonly used technology is the Radio Frequency Identification at 38.4 %, - which is showing promise but needs improvement. It is also evident from the literature that researchers combine Radio Frequency Identification with other technologies like Machine learning – 15.4 % and Blockchain – 7.7 %. It was evident that a lack of research on stakeholder experiences and perspectives is greatly overlooked, such as regulators, farmers, the government, and consumers. The review provides a clearer understanding of how different technologies interact within traceability ecosystems, highlighting gaps among technological potential and practical adoptions, offering actionable foundation for improved systems design and cross-sector decision-making.