An Innovative Shelf Life Model Based on Smart Logistic Unit for an Efficient Management of the Perishable Food Supply Chain. Issue 1 (3rd November 2015) - La Scalia, G.; Nasca, A.; Corona, O.; Settanni, L.; Micale, R.
Abstract: Despite the recent interest towards food safety and control, it is generally difficult to ensure full products traceability through industrial food chains, due to the lack of efficient information and communication systems. Consequently, nowadays, the protection of food products often ends at the gates of the producer without any investigation about the status of their quality at the consumer's location. The aim of this paper was the development of a supply chain monitoring system based on a smart logistic unit (SLU) to support the integrated management of the food supply chain from "farm to fork" in order to guarantee and control food safety and shelf life (SL) of products in agreement with logistic efficiency and system sustainability. For this purpose we have conducted a research involving the selection of a perishable product significantly affected by logistic decisions, the determination of the set parameters representative of its quality and the development of a prototype of SLU, based on a sensor network for monitoring the identified parameters. Finally, an experimental SL model has been determined, based on the volatile organic compounds emitted from fruits and monitored by the SLU. We have validated the model by simulating real transport conditions and assessing the residual SL of the product at different time intervals. Practical Applications: The practical application obtainable from our research is the development of a prototype of a smart logistic unit able to translate the acquired parameters into valuable information for supply chain management. In particular the proposed research establishes a correlation between volatile organic compounds and bacterial growth to obtain a mathematical model to predict the residual shelf life of the products and to assess the effects of vibration, caused by simulated transport. The knowledge of the residual shelf life in real time could finally be exploited for developing advanced supply chain strategies e.g., picking and transport routing policies.