Measurement and Prediction of Quality Attributes of ‘Golden Delicious’ Apples During Storage Using X-Ray Radiography Publisher



Tahani B ; Beheshti B ; Heidari Soltanabadi M ; Hekmatian E
Source: Applied Fruit Science Published:2025

Abstract

Apples are fruits that are often stored for extended periods. Evaluating and predicting the quality attributes of apples during storage can assist producers in selecting optimal storage conditions. In this study, ‘Golden Delicious’ apples were stored at 0 ° and 4 °C for 0, 45, 90, and 135 days, with measurements taken for quality attributes such as computed tomography (CT) number, pH, firmness, moisture content, density, and total soluble solids (TSS). The results showed that at 0 °C, the CT number, pH, firmness, moisture content, density, and TSS were −115.02, 3.85, 37.7 N, 0.82%, 0.767 g/cm3, and 15.30°Brix, respectively. At 4 °C, these values were −166.86, 3.86, 33.36 N, 0.806%, 0.721 g/cm3, and 15.79°Brix, respectively. This indicates that firmness, moisture content, and density decreased, while the absolute value of the CT number, pH, and TSS increased during storage. According to the results, apple firmness, moisture, and density showed a positive linear correlation with the CT number of the fruit and a negative linear correlation with the pH and dissolved solids. In the two storage temperatures of 0 ° and 4 °C, the coefficients of determination (R2) obtained from the regression models of the relationship between CT number and pH, firmness, moisture, density, and TSS were 0.73 and 0.56, 0.32 and 0.52, 0.86 and 0.95, 0.85 and 0.93, and 0.85 and 0.64, respectively. These findings suggest that non-destructive X‑ray radiography can be effectively employed to estimate certain quality attributes of apples with reliable accuracy. According to the results, polynomial and exponential regression models performed better than linear and logarithmic regression models in predicting apple quality characteristics using CT number. © 2025 Elsevier B.V., All rights reserved.