|M.Sc Student||Michaelis Ran|
|Subject||Prediction Model of the Mechanical Damage in Apples during|
Transportation and Handling
|Department||Department of Civil and Environmental Engineering||Supervisor||Professor Emeritus Itzhak Shmulevich|
|Full Thesis text - in Hebrew|
Mechanical damage caused to fruit during the processes of handling and transportation has always been a problem for growers and retailers. In apples, the mechanical damage, bruising, leads to degrading of the fruit and disqualifying it for marketing. In Israel about 30% of apples are rejected for export due to brusing. In the US alone, during 2007, more than 1.5 million fresh apples were sold with the estimated value of one billion USD. That is only about 10% of the world's annual apple produce. Modern transportation techniques, and the growing global markets, constantly increase quality demands of fresh fruit, thus emphasizing the economical consequences of bruising.
The goal of this research is to develop a numerical tool capable of predicting bruises caused during transportation and handling processes of apples.
The bruise prediction tool is based on a 3D numerical model using the Discrete Element Method (DEM), and on a statistical bruise prediction model by which the results of the DEM model are analyzed. As part of the research, a monitored pendulum device was designed, enabling to extract necessary data for determining mechanical properties of the apples, and the database required for the statistical bruise prediction model. Another experiment system was constructed to enable the validation and verification of the bruise prediction tool, by comparing the predicted bruising with actual measured bruising caused during vibration experiments on bulks of apples. The tool presented in the current work differs from other tools in the following aspects: Geometric representation of the apples; The contact model used in the DEM model; The bruise prediction model.
The developed prediction tool is capable of simulating transportation and handling conditions applied to apple bins in actual processes, and quantifying them in means of the amount of bruising the process causes to the produce. It could be used to examine effects of different parameters, such as number of apples per bin, or road condition, and assess their contribution to total bruising in the process. The tool was designed in a way that only two geometric parameters are required for describing the fruit, and two mechanical parameters for modeling the contact interactions. Loads and constrains applied to the bulk are also needed.
Testing the global performance of the bruise prediction tool with more complex vibration experiments, and applying it to other bruise sensitive fruit, will validate the prediction capabilities of the tool.