Development of a food temperature prediction model for real time food quality assessment. (February 2019)

• Record Type: Journal Article
• Authors: Song, Hajin; Kim, Jiyoung; Kim, Byeong-Sam; Koo, Junemo
• Is Part Of: International journal of refrigeration. Volume 98(2019)
• Page Start: 468
• Page End: 479
• Publication Date: 2019-02
• Subjects: Food temperature model -- Freshness monitoring model -- Real-time food quality monitoring system -- Heat transfer coefficient -- Thermal network; Modèle de température des aliments -- Modèle de surveillance de la fraîcheur -- Système de surveillance de la qualité des aliments en temps réel -- Coefficient de transfert de chaleur -- Réseau thermique; Refrigeration and refrigerating machinery -- Periodicals; 621.56
• DOI: 10.1016/j.ijrefrig.2018.11.032
• Languages: English
• ISSNs: 0140-7007

Abstract

Highlights: Models to relate the surrounding and food temperatures was developed and verified. Multilayers model was used to consider the spatial temperature distribution. Spatial distribution of heat transfer coefficient was analyzed using simulation. Abstract: Multilayer food temperature models considering the spatial temperature distribution in the food were developed to predict temporal temperature changes experienced by food during distribution considering the surrounding temperature, initial food temperature, and the predetermined surface heat transfer coefficient. Parameters used in the models were determined using the results of unsteady three-dimensional computational fluid dynamics simulations for the conjugated heat transfer problem between the food and surroundings. Models were validated by comparing model predictions with the food temperature experimentally measured under fluctuating temperature conditions with a mean absolute deviation of less than 1 °C. The developed food temperature model was integrated with a freshness monitoring model to complete the real-time food quality monitoring system. Food quality prediction using the integrated food quality monitoring system was validated for eggs and milk. Quality predictions using the food temperature model showed better accuracy than when using a single point measurement of food temperature.