Design of FBG-Based Sensing System for Meat Quality Assessment and Steak Cooking Optimisation

Abstract

Water presence in raw meat not only degrades its quality by diluting the natural flavours, but also increases the risk of bacterial growth, altering texture, and juiciness which ultimately affects the quality of end products. Therefore, quality assessment of raw meat in markets as well as in eateries is important to ensure the consumer's safety and satisfaction. In this paper, we propose a nondestructive technique to detect water presence in raw meat and steak cooking temperature optimisation using a fibre Bragg grating (FBG) temperature sensor inserted into the piece of raw meat. The contribution of this paper is twofold: First, the water presence in the piece of raw meat is detected by analysing the shift in Bragg wavelength corresponding to time-dependent gradual decrease in temperature of heated probe of FBG sensor due to convective heat transfer from probe to meat. Secondly, the optimum cooking temperature of a particular type of steak is achieved after quality assessment of meat by analysing the shift in Bragg wavelength corresponding to time-dependent gradual increase in probe temperature due to convective heat transfer from meat to probe. The results show that the proposed sensing system can complete the error-free detection of water in 250 g piece of raw meat within 30 s for water contents of 50, 75, and 100 g which account for 20%, 30%, and 40% of the net weight of meat, respectively. Moreover, the simulated and experimental values of temperature sensitivity (TS) of FBG sensor used in this work are around 13 and 10 pm/°C, respectively. The proof of the concept of a smart restaurant based upon the proposed work is also discussed. This study provides a nondestructive, simple, and fast solution for detection of water in raw meat and achieving the optimum cooking temperature for different types of steaks.