A New Acoustic-Based Approach for Assessing Induced Adulteration in Bovine Milk

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 i...

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Bibliographic Details
Published in:	Sensors (Basel, Switzerland) Vol. 21; no. 6; p. 2101
Main Authors:	Messias Dos Santos Junior, Marcos, Albuquerque de Castro, Bruno, Ardila-Rey, Jorge Alfredo, de Souza Campos, Fernando, Merino de Medeiros, Maria Izabel, Covolan Ulson, José Alfredo
Format:	Journal Article
Language:	English
Published:	Switzerland MDPI 17-03-2021 MDPI AG
Subjects:	Acoustics Animals bovine milk adulteration Cattle Drug Contamination Food Contamination - analysis instrumentation systems Milk piezoelectric transducers signal processing analysis Urea piezoelectric transducers signal processing analysis bovine milk adulteration instrumentation systems
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Summary:	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 × 10 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.
ISSN:	1424-8220 1424-8220
DOI:	10.3390/s21062101