Impacto de la ciencia de datos y blockchain en la trazabilidad y la prevención del fraude en la cadena de suministro agroalimentaria.

Resumen

The agri-food supply chain faces growing challenges in traceability, transparency, and fraud prevention, driven by its high fragmentation, the diversity of participating stakeholders, and the limited integration of traditional information systems. These constraints generate information asymmetries, erode trust among actors, and hinder the efficient control of product and data flows. In this context, data science and blockchain emerge as complementary approaches with strong potential to transform information management and reinforce trust across the supply chain. This study examines the impact of their integration on improving traceability and fraud prevention in the agri-food sector. Blockchain-based infrastructures significantly enhance the integrity, reliability, and availability of information, while also enabling the early detection of anomalies and fraudulent behavior. The research adopts an analytical and exploratory approach, grounded in a review of academic literature and a comparative analysis of conceptual models, technological architectures, and documented application cases within the agri-food domain. The findings indicate that blockchain strengthens traceability, whereas data science provides predictive analytics, anomalous pattern detection, and decision-support capabilities. Nevertheless, challenges remain regarding scalability, implementation costs, and data governance, which warrant further attention in future research.