An Empirical Model for Predicting the Fresh Food Quality Changes during Storage

Area of Science:

• Agricultural Science
• Food Science
• Horticultural Science

Background:

• Fruit quality attributes like firmness and weight loss are critical for assessing post-harvest value.
• These attributes are significantly influenced by transportation and storage conditions.
• Limited research exists on predicting fruit quality changes based on storage parameters.

Purpose of the Study:

• To investigate the impact of different cooling temperatures on the quality attributes of four apple cultivars.
• To develop a predictive model for apple quality changes during storage as a function of temperature and time.

Main Methods:

• Experimental analysis of weight loss and firmness in Granny Smith, Royal Gala, Pink Lady, and Red Delicious apples.
• Storage at controlled temperatures ranging from 2°C to 8°C.
• Development and validation of a multiple regression model to predict quality attributes.

Main Results:

• Firmness consistently decreased over time across all cultivars, with a slower decline at lower temperatures (2°C).
• Weight loss increased with time, showing a strong correlation.
• The developed predictive model demonstrated excellent accuracy (R² = 0.9544) in forecasting quality changes.

Conclusions:

• Temperature significantly impacts apple firmness, with 2°C being the most effective for quality preservation.
• The developed multiple regression model provides a reliable tool for predicting apple quality during storage.
• Stakeholders in the fruit industry can utilize this model to anticipate quality changes and optimize storage strategies.