Mapping the postharvest life of imported fruits from packhouse to retail stores using physics-based digital twins

Abstract Controlling the hygrothermal conditions around fresh fruit and vegetables is vital for their preservation. Therefore, cold chain stakeholders often measure temperature along the supply chain of fresh produce. However, the temperature is typically monitored only in one segment of the entire cold chain, namely from the supplier until the distribution center. Besides, such measured data are rarely used for decision-making because they are not translated into the impact on the quality of the products. We provide a solution by extending the monitoring until the retail stores and upcycling these thermal data into actionable metrics. To do so, we use physics-based digital twins, namely virtual representations of the food products. This study focuses on 331 cold chain shipments of cucumber, eggplant, strawberry, and raspberry imported from Spain to Switzerland. We followed these fruits through pre-cooling, thermally stable conditions at the distribution center, and the temperature ramp-up phase before arriving at the retail store. The temperature performance of each carrier and flow analysis of the shipment enabled us to map the complex logistic system better. The digital twins detected that the fruits lost 43 - 85% of their quality before being displayed at the retail store. This quality loss remains invisible to the retailer. Additionally, we found a strong correlation between fruit quality and shipment duration (i.e., for cucumber r = -0.95 (P