The aim of the study was the development of a quality prediction model combined with the incoming analysis for temperature control in 18 degree ready-to-eat food during logistics flows. And analyzed how temperature monitoring improves inventory decision. Base on the growth of Pseudomonas sp., the model was developed by mathematical model with Gompertz model. The model predicts for quality as well as shelf life in the monitoring temperature is about 19.5 h. On the other hand, the incoming analysis shows that the inventory quantities at 7 ℃ and 18 ℃ is more than at 25 ℃. The model can be considered to be an effective tool (in combination with temperature monitoring) for improvement of quality management with the incoming consideration. Moreover, our results suggest that temperature-controlled food companies could share temperature information with its chain partners which emphases a food quality and logistics cost balance in supply chain.


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