Abstract
There are currently limited options for the meat producers for monitoring the water content of their products as they are processed or cured. Most existing methodologies are destructive, or require the use of probes which touch or penetrate the meat and lead to issues of contamination and damage. Thus, the aim of this investigation is to use an electromagnetic (EM) wave sensor to monitor the meat drying process and determine its suitability as a non-destructive and non-contact technique. The sensor has been modelled using High Frequency Structure Simulation Software (HFSS) and then constructed. Experimental work was conducted involving measurement of meat weight and EM signature (namely the S11 parameter in the frequency range 1–6 GHz) over a period of approximately 1 week, with measurements recorded every hour. The change in EM signature and weight loss has been analysed and correlations drawn from the resultant data. The results demonstrate a strong relationship between the S11 measurement and weight loss of the meat sample (R2 = 0.8973), and it is proposed that this could be used as the basis for future industrial application for measuring meat products during drying processes, such as those used in curing.
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Notes
- 1.
The “Spektron” device launched recently by Prediktor (http://www.prediktor.no/) is a good example of an online system designed for this function.
- 2.
Tomra (http://www.tomra.com/) have the “ODENBERG QVision 500” sensor system for online monitoring and sorting of meat products on the basis of bulk fat content.
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Acknowledgments
The authors thank Chechen Ministry of Education and Science and Chechen Government for their support during the PhD research. Furthermore, the authors thank the members of the INFORMED EUREKA project consortium for their continued support of LJMU researchers in this application of their sensor technology.
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Muradov, M., Cullen, J., Mason, A. (2016). Real-Time Monitoring of Meat Drying Process Using Electromagnetic Wave Sensors. In: Mukhopadhyay, S. (eds) Next Generation Sensors and Systems. Smart Sensors, Measurement and Instrumentation, vol 16. Springer, Cham. https://doi.org/10.1007/978-3-319-21671-3_10
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