Developing a predictive model of salted kimchi cabbage shelf-life using the general stability index

Abstract

Salted kimchi cabbage (SKC) is a ready-to-use product used to manufacture kimchi. However, during distribution and storage, deterioration in quality parameters, such as pH, total titratable acidity, aerobic plate count, and color, lowers the product value. To ensure sufficient distribution and consumer storage, SKC should be vacuum-packed and cold-stored. Therefore, in this study, changes in SKC quality parameters were monitored at different cold storages (≤10 °C), and a predictive model of SKC shelf life was established using the general stability index (GSI) method. The established GSI method is an adequate tool for predicting the shelf life of SKC. The model with the highest R2 value was obtained by fitting the data with a second-order equation and integrating it with 0–10 °C using the Arrhenius equation. This study provides important insights into the quality assessment and shelf-life prediction of SKC during cold storage, contributing toward quality management systems. In addition, chromaticity values, which previously lacked reproducible measurement methods for SKC, were obtained after segmenting complex-shaped parts using a novel image analysis technique. This technique can be applied to a variety of vegetables to determine chromaticity of individual parts for assessing quality based on symptoms like browning.