2017 Volume 23 Issue 4 Pages 545-549
The severity of internal browning in apple cultivars is often evaluated subjectively, making it potentially unreliable, and a method for automatic evaluation is necessary in order to process many samples efficiently. The objective of this study was to propose a model for estimating subjective browning severity ratings (SBSRs) in scanned images of sliced apples that mimics mean expert judgments. We assessed SBSRs made by three expert observers for images of sliced apples. The results indicated that the experts' evaluations of internal browning were qualitatively similar, but not quantitatively equivalent. The proposed model estimates the mean SBSRs of experts as a percentage of the browning region of the total flesh. The browning regions were qualified using CIELAB color difference from the standard color. The model estimations were consistent with increasing browning during longer storage periods.
