Mapping fruit quality variabilities within refrigerated unit operations of fresh fruit supply chains using multiphysics modeling and high-resolution sensing

Fresh fruit stay alive after harvest. To maximally maintain their quality, the storage conditions, like temperature and relative humidity, must remain well controlled within the postharvest supply chain. However, postharvest supply chains consist of many unit operations, such as transport or storage. Moreover, these operations are densely loaded with fruit pallets, such that non-uniform conditions or local hotspots can develop, which negatively impact the fruit quality maintenance. Currently, there is no high-resolution understanding of what is happening to fruit within commercial supply chains.

The main objective of this thesis was to optimize the citrus and pear fruit supply chain by mapping temperature and fruit quality variabilities developed within specific postharvest unit operations. This was done by using both numerical and experimental techniques. The unit operations studied included refrigerated transport (trailer and container transport) and innovative storage techniques (RQ-DCA and hypobaric storage). By mapping temperature or fruit quality variability during transport, the aim was to pinpoint where and when fruit quality is currently lost. Moreover, new innovative storage techniques are being developed which can replace the current storage techniques for improved fruit quality maintenance during long-term storage. To optimize their operation and facilitate the upscaling of these new techniques to a commercial scale, the variability within these operations was studied. The results of this thesis contribute to minimizing food losses and can enable more sustainable fresh fruit supply chains.