Shelf-life (SL) prediction and Least Shelf-life First Out (LSFO) stock strategy are important factors in perishable food supply chain in order to reduce quality and economic losses. In particular, distribution represents one of the main critical phases in logistic chain management and only the introduction of monitoring procedure can allow a reduction in food losses. Literature shows several mathematical models for analysing the changes in food quality using environmental/product parameters. However, these models can be very useful decision support tools only if the abovementioned parameters can be processed in real time. This paper focuses on technologies and applications to acquire and monitor changes in product shelf life using different SL predictive models. The paper includes a case study on a simulated transportation of strawberries, using a prototype of Smart Logistic Unit equipped with a GPS module for real time positioning of the truck, a 3G connection as communication system for remote quality supervision, and a shelf life prediction algorithm based on four different models and implemented on a webGIS platform.
|Numero di pagine||9|
|Rivista||Computers and Electronics in Agriculture|
|Stato di pubblicazione||Published - 2016|
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