Effective Data Technology for Quality Monitoring and Logistic Decision Support in Cold Chains of Fresh Agricultural Products

Effective Data Technology for Quality Monitoring and Logistic Decision Support in Cold Chains of Fresh Agricultural Products

Effective monitoring of quality indicators along the fresh produce cold chain is a crucial mechanism for not only maintaining food quality and safety levels but also reducing the considerable food losses that customarily occur along the greater food supply chain. This research study proposes the development of a comprehensive cold chain monitoring ‘solution’, in the form of a system and process that accounts for and integrates factors beyond the common focus for cold chain monitoring, thus spanning fresh produce quality attributes, storage and environmental conditions, handling processes, and logistics operations.

Taking advantage of the currently growing Internet of things technology and big data analytics, the study is using a systems approach to develop data-driven models of the links between the abovementioned cold chain factors and their effects on the cold chain in terms of food quality and losses. A real-time monitoring platform that generates actionable information is being developed, with the aim of minimising food losses through improving cold chain operations, including via increased levels of transparency and enabling proactive intervention by cold chain players.