Bruising of the subcutaneous tissues of blueberries is an important form of mechanical damage. Different levels of bruising have a significant effect on the post-harvest marketing of blueberries. To distinguish different grades of blueberry bruises and explore the effects of different factors, explicit dynamic simulation and near-infrared hyperspectral reflectance imaging were employed without harming the blueberries in this study. Based on the results of the compression experiment, an explicit dynamic simulation of blueberries was performed to measure the potential locations of bruises and preliminarily divide the bruise stages. A near-infrared hyperspectral reflectance imaging system was used to detect the actual blueberry bruises. According to the blueberry photos taken by the near-infrared hyperspectral reflectance imaging system, the actual bruise rates of blueberries were obtained by using the Environment for Visualizing Images software for training and classification. Bruise grades of blueberries were divided accordingly. Response surface methodology was used to determine the effects of ripeness, loading speed and loading location on the blueberry bruising rate. Under the optimized parameters, the actual damage rate of blueberries was 1.1%. The results provide an important theoretical basis for the accurate and rapid identification and classification of blueberry bruise damage.
Blueberries are prone to mechanical damage during the processes of grading, packaging, transportation, and selling, and stack damage is one of the important causes of blueberry quality loss. The mechanical parameters of blueberry should be obtained firstly to create the mechanical model for analyzing the stack problems of multilayer blueberries. Precise mechanical parameters were obtained for the first time by performing a compression experiment and analyzing an explicit dynamics simulation based on the finite element model. It was found that the elastic modulus of the blueberries was 0.225 MPa and that the Poisson's ratio of the blueberries was 0.35. The placement direction of the blueberries had the greatest impact on the rupture force, followed by the number of stacked layers and the loading speed. A regression model
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