Evaluation of enzymatic browning in fresh-cut apple slices applying a multispectral vision system

Abstract

n this study a vision system was applied for assessing enzymatic browning evolution in fresh-cut apples slices stored at 7.5 °C and 85 % HR. Twenty-four slices were analyzed per day: at zero time and after storage for 1 , 3 ,7 and 9 days. A classification procedure was applied to virtual images obtained as a combination of the red (R) and blue (B) channel (B/R, R-B and R-B/R+B). In all cases, three images based browning reference classes were generated. An external validation was applied to a second set of samples submitted to the same treatments, obtaining a high percentage of samples correctly classified. Camera classification was evaluated according to colorimetric measurements usually utilized to evaluate enzymatic browning: CIE L*a*b* colour parameters and browning index (Bl). Virtual image based on B/R showed the best sensitivity to reflect the change in colours associated with brownin