Relationship of Textures from Tomato Fruit Images Acquired Using a Digital Camera and Lycopene Content Determined by High-Performance Liquid Chromatography
2022
Ewa Ropelewska | Justyna Szwejda-Grzybowska
This study aimed at correlating image features with the lycopene content of tomato fruit. Tomato cultivars with different fruit colors, such as &lsquo:Oż:arowski&rsquo: (yellow), &lsquo:Marvel Striped&rsquo: (yellow-orange-pink), &lsquo:Green Zebra&rsquo: (green), Sandoline F1 (red), Cupidissimo F1 (red), and Sacher F1 (brown) were selected for the study. The tomato fruits were imaged using a digital camera. The texture parameters were computed from the images converted to color channels R, G, B, L, a, b, X, Y, and Z based on the histogram, autoregressive model, gradient map, co-occurrence matrix, and run-length matrix. Lycopene content was determined using high-performance liquid chromatography (HPLC). Pearson&rsquo:s correlation coefficients (R), regression equations, and coefficients of determination (R2) were determined. The lycopene content in fruit ranged from 0.31 mg 100 g&minus:1 for &lsquo:Green Zebra&rsquo: to 11.83 mg 100 g&minus:1 for Sacher F1. The correlation coefficient (R) between lycopene content and selected image textures reached &minus:0.99 for selected textures from color channels G, b, and Y. The highest positive correlation (R parameter equal to 0.98) was obtained for texture from color channel Y. Based on the individual color channel providing the highest results, one texture was selected for the determination of regression equations. Coefficients of determination (R2) of 0.99 were obtained for texture from color channel G. The regression equations may be used in practice for nondestructive, objective, and precise estimation of the lycopene content in tomato fruit.
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