Description of the kinetic enzymatic browning in fresh- cut Golab apple slices using different methods of digital image analysis

The objective of the study was to assess the ability of image analysis described in enzymatic browning kinetics of apple using fractal dimension (FD) and gray level co-matrix (GLCM) and compare it with color indicators such as average L* value (conventional method). The Fourier fractal texture image was used to calculate a fractal dimension value (FD). Power-law model used to model the enzymatic kinetic. The results showed that the average of L* value decreased during an enzymatic browning in fruit slices, while FDL* rose. Results showed that it is possible to use GLCM image texture to describe the browning kinetic, because the surface intensity in image becomes more jagged and local variation in color intensity are distributed non- homogeneously on the image during browning. Image texture gives us information about the spatial arrangement of color or intensities in an image that was not recorded when the traditional (L* value) method was used. Changes in the histogram of image intensities was studied and the resulted showed during browning, image histogram towards the apple generally darker gray levels change while the changes are not uniform, which represents the greater intensity of browning at some points.