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. 2014 May 5;372(2017):20130308.
doi: 10.1098/rsta.2013.0308. Print 2014 Jun 13.

Quality tracing in meat supply chains

Miriam Mack  1 , Patrick Dittmer, Marius Veigt, Mehmet Kus, Ulfert Nehmiz, Judith Kreyenschmidt
Affiliations

Quality tracing in meat supply chains

Miriam Mack et al. Philos Trans A Math Phys Eng Sci. .

Abstract

The aim of this study was the development of a quality tracing model for vacuum-packed lamb that is applicable in different meat supply chains. Based on the development of relevant sensory parameters, the predictive model was developed by combining a linear primary model and the Arrhenius model as the secondary model. Then a process analysis was conducted to define general requirements for the implementation of the temperature-based model into a meat supply chain. The required hardware and software for continuous temperature monitoring were developed in order to use the model under practical conditions. Further on a decision support tool was elaborated in order to use the model as an effective tool in combination with the temperature monitoring equipment for the improvement of quality and storage management within the meat logistics network. Over the long term, this overall procedure will support the reduction of food waste and will improve the resources efficiency of food production.

Keywords: logistics network; meat quality; predictive model; quality driven distribution; shelf life; temperature monitoring.

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Figures

Figure 1.
Figure 1.
(a) Shelf life of vacuum-packed lamb as a function of temperature (filled squares) at 2°C, 7°C, 15°C and 20°C. (b) Modelling temperature dependency of slope steepness b of quality index with Arrhenius equation (filled squares) ln(b) estimated in primary modelling step (solid line) ln(b)=30.50−9876.57×1/T (R2=0.978).
Figure 2.
Figure 2.
Cold chain of Irish lamb products with cross-docking facilities (depot and warehouse).
Figure 3.
Figure 3.
Data management with ICLogistics.
Figure 4.
Figure 4.
Concept for quality tracing in the lamb supply chain with the warehouse as centre of decision-making.
Figure 5.
Figure 5.
Impacts of quality tracing on logistics processes of cold chains; QI, quality index; QID, quality index at the time of delivery; QIE, quality index at the end of shelf life; t, time; tD, end of delivery (target); tDnew, end of delivery (actual).
See this image and copyright information in PMC

References

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