# Quality Assessment of Banana Ripening Stages by Combining Analytical Methods and Image Analysis
## 3 Results and Discussion  
Classification of the Banana According to Ripening Process of Peel and Flesh Using Textural Image Analysis  
Image analysis provided a non-invasive and rapid method for evaluating the quality and ripeness of the bananas. The gradual differentiation in the peel appearance and color of the banana samples during 21 days of storage, as captured by image analysis, is illustrated in Figure 1.  
Machine-learning methods were employed on the computed features arising from the colored images of the banana peel, as well as from the grayscale images of the banana peel and of flesh after iodine testing, in order to examine variations in image texture during fruit ripening. Concerning the banana peel (Figure 2), statistically significant changes related to ripening were noted in the following features: lightness (L*), parameter a* (green to red), parameter b* (blue to yellow), mean, standard deviation, contrast, dissimilarity, energy, homogeneity, ASM, SRE, LRE, and RLN. Figure 1: Representative images of the banana peel over a period of 21 days (i.e., days 2, 4, 7, 9, 11, 14, 17, 21) during fruit storage and ripening. Figure 2: Cont. Figure 2: _Cont_. Regarding the colored images of the banana peel, significant changes were observed in all extracted features. Specifically, during peel storage, the lightness and b* parameters showed a significant (\(p<0.05\)) decreases, whereas the a* parameter had a significant (\(p<0.05\)) increase (Figure 2, Table S1). Based on these results, it appeared that as ripening progressed, the banana peels increased in redness, converted from yellow to dark blue, and lost their luminosity. These findings were in accordance with the results of [PERSON] and [PERSON] [23], who had also reported that these changes were due to the breakdown of chlorophyll, leading to the development of brown spots. Regarding the grayscale version of the images of the banana peels, the increases in the standard deviation (the variation of the image gray levels from the mean value), contrast (the amount of local intensity variations in the image), dissimilarity (the image-texture variation), short-run emphasis (small structures of equal gray levels), and run-length non-uniformity (the non-uniformity of the structures in the image) values (Figure 2) indicated an uneven distribution among the gray levels of the image structures, potentially due to the appearance of smaller dark areas and spots on the banana peel during the storage period, resulting in an increase in gray-level inequality and the non-uniformity of the structures in  
Figure 2: Variations of image analysis computed features (lightness L*, a* parameter, b* parameter, mean, standard deviation, skewness, kurtosis, contrast, dissimilarity, energy, homogeneity, correlation, angular second moment (ASM), short-run emphasis (SRE), long-run emphasis (LRE), gray-level non-uniformity (GLN), run-length non-uniformity (RLN) and run percentage (RP)) of the banana peel samples, according to storage intervals of 2, 4, 7, 9, 11, 14, 17, 21 days. the images. The gradual development of dark areas and spots on the banana peels during ripening are shown in Figure 1. Interestingly, the box plot of the run-length non-uniformity feature during the storage period tended to classify the banana peel samples according to three degrees of increasing ripeness: the interval up to day 4, the interval between days 7 and 11, and the interval between days 14 and 21. The decrease in the mean (the mean value of the intensities of all image pixels), energy (image gray-level homogeneity), homogeneity (image gray-level homogeneity), angular second moment (homogeneity of the original image), and long-run emphasis (large structures of equal gray level) values (Figure 2) indicated an increase in image dissimilarity and the loss of the texture structural order that was probably due to the appearance of darker spots and areas on the banana peel during the storage period.