Rapid detection of milk adulteration using Raman spectroscopy and statistical modelling

  • Anca Becze INCDO-INOE2000, Subsidiary Research Institute for Analytical Instrumentation, ICIA, Cluj-Napoca
  • Dorina Simedru INCDO-INOE2000, Subsidiary Research Institute for Analytical Instrumentation, ICIA, Cluj-Napoca
DOI: https://doi.org/10.35219/ann-ugal-math-phys-mec.2022.2.10
Keywords: milk, food adulteration, Raman spectroscopy, Minitab, statistical modelling, PLS

Abstract

Food adulteration has become a concern for consumers and food safety authorities. Milk is a commune adulterated food product, like melamine adulteration, which resulted in devastating effects, especially on young children. Because of the current fast paste economy, it is essential to develop equally fast analysis methods to ensure reliable and sensitive results quickly with little to no sample preparation. For that purpose, a Raman method was developed and Partial least squares regression (PLS) was applied in order to develop a model for adulterated goat milk detection. Minitab 17 software was used for the statistical modeling of data. Validation matrices were constructed using unadulterated goat milk and goat milk adulterated with cow milk in different proportions (0-50%). The prediction model had a correlation coefficient of 99.8 %.

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Published
2022-12-12
How to Cite
Becze, A. and Simedru, D. (2022) “Rapid detection of milk adulteration using Raman spectroscopy and statistical modelling”, Analele Universității ”Dunărea de Jos” din Galați. Fascicula II, Matematică, fizică, mecanică teoretică / Annals of the ”Dunarea de Jos” University of Galati. Fascicle II, Mathematics, Physics, Theoretical Mechanics, 45(2), pp. 104-109. doi: https://doi.org/10.35219/ann-ugal-math-phys-mec.2022.2.10.
Issue
Vol 45 No 2 (2022): Volume dedicated to the memory of Assoc. prof. dr. math. Mihaela Baroni (1964-2022),
Department of Mathematics and Informatics, Faculty of Sciences and Environment
Section
Articles