Shelf life prediction based on sensor data in cold chain

Klemen Marolt (2016) Shelf life prediction based on sensor data in cold chain. MSc thesis.

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Abstract

It is estimated that every year one third of produced food is wasted worldwide during the supply chain. One of the main reasons for such situation is non-compliance with conditions of storage of perishable food. In order to ensure adequate quality it is important to maintain a required temperature during the whole cold chain. We developed a model for dynamic prediction of shelf life for fish that is packed in a box made of styrofoam and covered with ice. Various tests were made where environment and fish temperatures were measured during the storage and transport processes. Arrhenius model, model CSIRO and SAL table were used for prediction and analysis of shelf life which is a function of time and fish temperatures. Comparison of the results together with dynamically changing shelf life and existing tests data were used for model development. At first fish temperatures are calculated from environment temperatures. These are used for remaining shelf life calculation during the cold chain process. An application was developed for mobile RFID reader for practical use on the field. It reads data from RFID module SL900A, displays dynamically changing environment temperatures and predicts remaining shelf life.

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