Relationship of Textures from Tomato Fruit Images Acquired Using a Digital Camera and Lycopene Content Determined by High-Performance Liquid Chromatography

Ewa Ropelewska () and Justyna Szwejda-Grzybowska
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Ewa Ropelewska: Fruit and Vegetable Storage and Processing Department, The National Institute of Horticultural Research, Konstytucji 3 Maja 1/3, 96-100 Skierniewice, Poland
Justyna Szwejda-Grzybowska: Fruit and Vegetable Storage and Processing Department, The National Institute of Horticultural Research, Konstytucji 3 Maja 1/3, 96-100 Skierniewice, Poland

Agriculture, 2022, vol. 12, issue 9, 1-12

Abstract: This study aimed at correlating image features with the lycopene content of tomato fruit. Tomato cultivars with different fruit colors, such as ‘Ożarowski’ (yellow), ‘Marvel Striped’ (yellow-orange-pink), ‘Green Zebra’ (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’s correlation coefficients (R), regression equations, and coefficients of determination (R 2 ) were determined. The lycopene content in fruit ranged from 0.31 mg 100 g −1 for ‘Green Zebra’ to 11.83 mg 100 g −1 for Sacher F1. The correlation coefficient (R) between lycopene content and selected image textures reached −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 (R 2 ) 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.

Keywords: tomato cultivars; fruit color; tomato lycopene; image analysis; correlation; regression (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2022
References: View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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