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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.

Keywords

Cold chain Shelf life Prediction Fish supply chain 

Notes

Acknowledgments

This work has been supported by Slovenian research agency under ARRS Program P2-0359 Pervasive computing and in collaboration with Fonda.si which provided the data.

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Copyright information

© ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2018

Authors and Affiliations

  1. 1.Faculty of Computer and Information ScienceUniversity of LjubljanaLjubljanaSlovenia

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