EventsThe 6th International Electronic Conference on Foods
Published
This submission belongs to the session C. Food Quality and Safety of the event The 6th International Electronic Conference on Foods
Published date
27 Oct, 2025
Academic Editor
author-avatarSusana Casal
Citation
Ewa Ropelewska, Justyna Szwejda-Grzybowska, Anna Wrzodak, Relationships Between Physicochemical Properties and Image Texture Features of Yellow Sweet Bell Pepper after Selected Periods of Spontaneous Lacto-fermentation, in Proceedings of The 6th International Electronic Conference on Foods, 28 October–30 October 2025, MDPI: Basel, Switzerland
Share
Email
Facebook
Twitter
LinkedIn

Relationships Between Physicochemical Properties and Image Texture Features of Yellow Sweet Bell Pepper after Selected Periods of Spontaneous Lacto-fermentation

image
1. Fruit and Vegetable Storage and Processing Department, The National Institute of Horticultural Research, Konstytucji 3 Maja 1/3, 96-100 Skierniewice, Poland, Poland
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
Poster
sciforum-128134.pdf
Evaluation of raw materials derived from agro-wastes for the manufacture of iron controlled-release systems
Microbiological evaluation of seaweed-enriched meatballs as a strategy to enhance iodine intake