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Relationships Between Physicochemical Properties and Image Texture Features of Yellow Sweet Bell Pepper after Selected Periods of Spontaneous Lacto-fermentation
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1  Fruit and Vegetable Storage and Processing Department, The National Institute of Horticultural Research, Konstytucji 3 Maja 1/3, 96-100 Skierniewice, Poland
Academic Editor: Susana Casal

Abstract:

Lacto-fermentation is an effective method for preserving sweet bell peppers after harvest. In addition to extending their shelf life, this process enhances the peppers with beneficial health properties. The objectives of this study were as follows: (1) To determine the physicochemical properties, such as pH, acidity, total soluble solids, sugars, L-ascorbic acid, and carotenoids, and 2172 texture parameters from images in color channels R, G, B, S, U, V, X, Y, Z, L, a, and b, of yellow sweet bell pepper ‘Yellow California’ before lacto-fermentation and after 7, 14, 28, and 56 days of the process. (2) To determine the linear correlations between physicochemical properties and image texture features. Finally, (3) to set linear regression equations for estimating the changes in the physicochemical properties of yellow sweet bell pepper during lacto-fermentation based on image parameters. The correlation and regression were performed using STATISTICA 13.3 (StatSoft Polska Sp. z o.o., Kraków, Poland, TIBCO Software Inc., Palo Alto, CA, USA). Significantly strong relationships among the analyzed parameters were found. The values of correlation coefficient (R) reached 0.99 between glucose and image texture bS5SN3SumVarnc, and pH and VS5SV1Correlat; -0.99 between fructose and RHPerc99, total sugars and RHPerc99, L-ascorbic acid and RHPerc99, and total soluble solids and RHPerc99; 0.98 between ß-carotene and US5SH1Entropy, and sucrose and US5SH3Entropy; and -0.98 between ß-carotene and aHMaxm10. The developed regression equations allowed for predicting physicochemical parameters based on image textures with high coefficients of determination (R2) of up to 0.98. The models were validated and tested using independent data, which confirmed their effectiveness.

Funding: This research is part of project No. 2023/07/X/NZ9/01642, “Determination of the relationship between the parameters of the images and the chemical properties of cucumber and pepper during fermentation” funded by the National Science Centre for the 7th edition of the MINIATURA call.

Keywords: sweet bell pepper; lacto-fermentation; image texture analysis; correlation; regression modeling
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