Simulations on the prediction of cod (Gadus morhua) freshness from an intelligent packaging sensor concept. (March 2015) - Heising, J.K.; van Boekel, M.A.J.S.; Dekker, M.
Highlights: A mathematical model was developed to predict the freshness of packed fish. The physical and (bio)chemical principles of TMA formed on fish are modelled. Differences in initial fish quality and dynamic temperatures are included in the model. Model simulations show that minimizing the sensor leads to improved sensitivity. The dynamic model can be used for an intelligent packaging sensor concept. Abstract: A non-destructive method that monitors changes in the freshness status of packed cod fillets has potential for the development of an intelligent packaging concept. The method is based on monitoring volatile compounds that dissolve and dissociate in the sensing aqueous phase. A mathematical model was developed to predict the freshness of the packed fish from the sensor signal (based on trimethylamine (TMA)). The model is based on physical and (bio)chemical principles of biological formation, mass transport, partitioning, and dissociation of TMA. The parameters in the model are derived partly from physical chemical properties, partly estimated from fitting the non-destructive sensor measurements in the aqueous phase and destructive TMA measurements in cod fillets. The model predicts a TMA increase in the aqueous phase comparable with sensor measurements from experimental storage trials. The initial freshness of fish is variable and taken into account in the model in the predictions of the freshness status of the packed fish. The model was used to test different scenarios for sensor design. This showed clearly that minimizing the aqueous phase will strongly improve the sensitivity of the sensor. Reducing the package headspace can further improve the sensitivity. In conclusion, the model can make accurate freshness predictions at a constant temperature of 0 °C and also in case of temporally temperature abuse, but needs a temperature-dependent correction for higher temperatures. Therefore combining the conductivity-sensor with a temperature sensor enables this model to be used in the development of an intelligent packaging to monitor the freshness of fish.