Modeling and Simulation of the Cooling and Heating Processes of Onions

Abstract

Abstract The shelf life of onions, or for that matter any food item, is defined as the time period where the produce has an acceptable quality and is safe to consume. For onion farmers and packers, the mode of determining the shelf life depends on the harvesting, drying, grading, packing, cooling, storing, and shipping processes and time. Quality loss can lead to economic loss as well as a decline in consumer confidence. Quality expectation should be maintained at an acceptable level for consumer purchase and consumption. In addition to post-harvest handling, the thermal history of the produce during storage and transportation plays a major part of shelf life and quality management. Due to the differences among onion varieties, some are more susceptible than others to damage resulting from temperature, high humidity, and other factors during processing. In general, the recommended storage temperatures range from 0 to 5 °C during cold storage and 20 to 30 °C during non-refrigerated storage. Both storage methods should have adequate air circulation of about 0.5 to 1.0 m3 of air per minute per 1.0 cubic meter of onions to maintain the temperature and prevent CO2 accumulation. In this study, the cooling and heating processes of different sizes of onions were conducted experimentally and numerically, and temperature readings were recorded. The cooling process was designed to simulate actual industry practice where cooling starts after the onions are placed in a cold storage room where the temperature is not constant. For the heating process, the experiment simulated industry practice where cold onions are transferred into a warm storage room where the temperature is uniform. These thermal environments are a common encounter during the storage and shipping of produce. Initially, the cooling and heating data were experimentally examined and used to estimate the cooling time as well as the cooling rate to gain an understanding of the heat transfer process. Furthermore, the data were used in evaluating the numerical simulation. In the case of small onions, the temperature changed from 21.1 to 4.4 °C after three and a half hours. However, in the case of large onions, a similar temperature change took nearly eight hours. The numerical simulation was conducted using 3D models and the thermal properties of the onions. This paper will discuss the experimental data and the CFD modeling and simulation. Based on this study, the thermal environment and critical time period that could cause changes in produce core temperature can be outlined and used to qualify thermal mishandling.