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The Canadian apple crop is hand picked, much of it by imported labor. If this labor force became unavailable, the Canadian apple processing industry would be in serious difficulty unless both growers and processors mechanize apple harvesting, handling and sorting. The main problem encountered in mechanically harvesting apples is bruising caused by impact of apples upon branches and upon other apples. Bruised apple tissue is un acceptable in processed products. Bruised areas are currently removed manually from the apples. Since mechanically harvested apples tend to have more bruises, this bruise recognition and removal operation would have to be mechanized also. In this study, different quality-index techniques, which utilize measured reflectance values at individual wavelengths, were intended to be used to recognize bruised tissue and to predict the bruise depth. Bruise depth is an important parameter for efficient automated removal of bruised apple tissue. Hence quality indicies were evaluated first by their ability to predict bruise depth. Quality indices were calculated by using: (1) average reflectance (2) reflectance at one narrow band width wavelength (3) reflectance values at two wavelengths (4) derivative values of reflectance at two wavelengths. They were then compared on their classification accuracy in predicting bruise depth and in distinguishing good and bruised apple tissue.
apple bruise detection using optical reflectance parameters
Bilanski, W. K., Pen, C. L. and D. R. Fuzzen 1984. APPLE BRUISE DETECTION USING OPTICAL REFLECTANCE PARAMETERS. Canadian Agricultural Engineering 26(2):111-114.
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