Milk is an important dietary requirement for many populations due to its high nutritional value. However, increased demand has also made it prone to fraudulent activity. In this sense, scientists have sought to develop simple, low-cost, and portable techniques to achieve quality control of milk in industry and farms as well. This work proposes a new instrumentation system based on acoustic propagation and advanced signal processing techniques to identify milk adulteration by industrial contaminants. A pair of transmitter-receiver low-cost piezoelectric transducers, configured in a pitch-catch mode, propagated acoustic waves in the bovine milk samples contaminated with 0.5% of sodium bicarbonate, urea, and hydrogen peroxide. Signal processing approaches such as chromatic technique and statistical indexes like the correlation coefficient, Euclidian norm and cross-correlation square difference were applied to identify the contaminants. According to the presented results, CCSD and RMSD metrics presented more effectiveness to perform the identification of milk contaminants. However, CCSD was 2.28 × 105 more sensitivity to distinguish adulteration in relation to RMSD. For chromatic clustering technique, the major selectivity was observed between the contamination performed by sodium bicarbonate and urea. Therefore, results indicate that the proposed approach can be an effective and quick alternative to assess the milk condition and classify its contaminants.
Sensors applied in the food industry are important tools for quality control. Current analyses checking adulteration in milk are expensive and time consuming, because the samples need to be evaluated in a laboratory environment. Thus, is important to develop methodologies and sensors to monitor milk production. A common type of fraud is performed adding substances such as sodium hydroxide in order to increase the shelf life of milk. In this study, we propose to use low-cost piezoelectric diaphragms transducers to implement a methodology that identifies milk adulteration using the mechanical waves propagation method (vibration and acoustic emission). Two piezoelectric diaphragms were used, the first was excited by a chirp signal with 1 V of amplitude and a frequency band since 0 to 65 kHz with 2 Hz of step, and concomitantly acquired the response signal of the second sensor installed in the opposite side of the actuator with a rate of 250 kHz. After acquiring the data, these were processed using the chromatic technique, which extracts three features: energy, average band and equivalent bandwidth, in order to classify the raw and the contaminated milk through clustering. The experimental results indicated that the methodology can differentiate between raw and contaminated milk with 1% of sodium hydroxide. Therefore, the results reported in this study indicate that low-cost piezoelectric diaphragms are promising for liquids quality control.
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