Technologies in cattle traceability: A bibliometric analysis

Abstract

It has been widely documented that livestock cattle can play a non-negligible role in natural landscapes due to climate change, deforestation, and enteric methane emissions. Alternatively, sustainable protocols and market digitalization are highlighted as promising tools to mitigate environmental cattle impacts by authenticated data in digital traceability systems. Digital inclusion, particularly for cattle breeders, can be a useful starting point for employing sustainable protocol in food chain production and management. This study analyzes the evolution of knowledge in the area of animal traceability to compare applied technologies found by a bibliometric analysis of articles published in Web of Science. The study evidences a clear change in thematic research over decades, currently culminating in technologies such as blockchain, IoT (Internet of Things), machine learning, and deep learning. These technologies emerge as the main research scopes in promoting transparency and reliability in the production chain, especially considering individual digital identification. However, challenges such as high investment requirements and difficulties in data accessibility, interoperability, privacy, and security implicate the low maturity level of available technologies and knowledge, therefore preventing further adoption and development of reliable worldwide animal traceability systems.