Cloud Infrastructures, Services, and IoT Systems for Smart Cities. Second EAI International Conference, IISSC 2017 and CN4IoT 2017, Brindisi, Italy, April 20–21, 2017, Proceedings

Research Article

Cold Chain and Shelf Life Prediction of Refrigerated Fish – From Farm to Table

  • @INPROCEEDINGS{10.1007/978-3-319-67636-4_9,
        author={Mira Trebar},
        title={Cold Chain and Shelf Life Prediction of Refrigerated Fish -- From Farm to Table},
        proceedings={Cloud Infrastructures, Services, and IoT Systems for Smart Cities. Second EAI International Conference, IISSC 2017 and CN4IoT 2017, Brindisi, Italy, April 20--21, 2017, Proceedings},
        proceedings_a={IISSC \& CN4IOT},
        year={2017},
        month={11},
        keywords={Cold chain Shelf life Prediction Fish supply chain},
        doi={10.1007/978-3-319-67636-4_9}
    }
    
  • Mira Trebar
    Year: 2017
    Cold Chain and Shelf Life Prediction of Refrigerated Fish – From Farm to Table
    IISSC & CN4IOT
    Springer
    DOI: 10.1007/978-3-319-67636-4_9
Mira Trebar1,*
  • 1: University of Ljubljana
*Contact email: mira.trebar@fri.uni-lj.si

Abstract

Fresh perishables are normally stored and distributed with a proper cold chain control in the supply chain from farm to retail. Usually, the consumers break the cold chain after the point of sale. The question is whether consumers are aware of requirements during the transport to and storage at home. The handling conditions and temperature changes can significantly decrease the shelf life and cause faster spoilage of food. The study presents two examples of shelf life prediction. The first one is based on temperature measurements of fish covered with ice in a Styrofoam box with supported information of environment temperatures in the cold store, uncooled car and refrigerator. In the second, measurements from first phase of storage on temperatures (0 °C–4 °C) were used with assumption of fish stored later on higher temperatures without ice. The results show important shortening of shelf life after the point of sale.