Freshly harvested horticultural produce require a proper temperature management to maintain their high economic value. Towards this end, low temperature storage is of crucial importance to maintain a high product quality. Optimizing both the package design of packed produce and the different steps in the postharvest cold chain can be achieved by numerical modelling of the relevant transport phenomena. This work presents a novel methodology to accurately model both the random filling of produce in a package and the subsequent cooling process. First, a cultivar-specific database of more than 100 realistic CAD models of apple and pear fruit is built with a validated geometrical 3D shape model generator. To have an accurate representation of a realistic picking season, the model generator also takes into account the biological variability of the produce shape. Next, a discrete element model (DEM) randomly chooses surface meshed bodies from the database to simulate the gravitational filling process of produce in a box or bin, using actual mechanical properties of the fruit. A computational fluid dynamics (CFD) model is then developed with the final stacking arrangement of the produce to study the cooling efficiency of packages under several conditions and configurations. Here, a typical precooling operation is simulated to demonstrate the large differences between using actual 3D shapes of the fruit and an equivalent spheres approach that simplifies the problem drastically. From this study, it is concluded that using a simplified representation of the actual fruit shape may lead to a severe overestimation of the cooling behaviour.
展开▼
