Abstract. Internal bruise damage that occurs in blueberry fruit during harvest operations and postharvest handling lowers the overall quality and causes significant economic losses. The main goal of this study was to nondestructively detect internal bruises in blueberries after mechanical damage using hyperspectral transmittance imaging. A total of 600 hand-harvested blueberries were divided into 20 groups of four storage times (30 min, 3 h, 12 h, and 24 h), two storage temperatures (22°C and 4°C), and three treatments (stem bruise, equator bruise, and control). A near-infrared hyperspectral imaging system was used to acquire transmittance images from 970 to 1400 nm with 5 nm bandwidth. Images were acquired from three orientations (calyx-up, stem-up, and equator-up) for fruit in the control and stem bruise groups and from four orientations (calyx-up, stem-up, equator-up, and equator-down) in the equator bruise groups. Immediately after imaging, the fruit samples were sliced, and the sliced surfaces were photographed. The color images of sliced fruit were used as references. By comparing with the reference color images, the profiles of spatial and spectral intensities were evaluated to observe the effect of orientation and help extract regions of interest (ROIs) of bruised and healthy tissues. A support vector machine (SVM) classifier was trained and tested to classify pixels of bruised and healthy tissues. Classification maps were produced, and the bruise ratio was calculated to identify bruised blueberries (bruise ratio >25%). The average accuracy of blueberry identification was 94.5% with the stem-up orientation. The results indicate that detecting bruised blueberries as soon as 30 min after mechanical damage is feasible using hyperspectral transmittance imaging. Keywords: Blueberry, Bruise detection, Classification, Hyperspectral imagery, Transmittance mode.
Near Infrared Cameras to Capture Full Color Images-A Study of Color Reproduction Methods Without an Infrared Cut Filter for Digital Color Cameras-
