Abstract
In the postharvest chain of fresh horticultural produce, it is often challenging to quantify how much potential measures improve the supply chain. This study compares and quantifies the impact of the different measures in preserving the quality of fresh produce in the cold chain. We employed physics-based digital twins of fresh produce. This digital twin is the virtual representation of fresh produce that can calculate the temperature distribution within the fruit and link these to quality decay based on the measured air temperature data. In this study, 95 shipments were monitored in the cold chain for four fruits (cucumber, eggplant, strawberry, and raspberry) imported from Spain to Switzerland. Using these temperature data as inputs for the digital twins, their hygrothermal response and physiological evolution to evaluate different optimization strategies were simulated. We showed that shortening the time length of shipment by one day at the distribution center resulted in 18% higher fruit quality index for cucumber and eggplant and 60% higher for berries. Lowering the shipment temperature by 5 °C extended the shelf life of strawberry on average by 36% and raspberry by 73%. Lowering the shelf temperature in retail stores by 5 °C prolonged the shelf life of the four fruits, on average, by about 40%, but the reduction is very fruit-dependent. For every 10% increase in relative humidity in the surroundings of unpacked fruit from during transport and at the distribution center by adjusting hygrothermal climate control, mass loss was reduced by 20% for all the studied fruits. Finally, evaporative cooling at the retail stores, which could be done by dry misting, extended the shelf life by more than 60%, due to the induced temperature reduction. Taking advantage of this digital twin's capability to evaluate the different scenarios, we can quantify the impact of cold chain optimizations more efficiently and cost-effectively in the design phase.
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