Principal component analysis for detection of melamine adulterated milk products

Abstract

Melamine is added to diluted milk to increase the nitrogen content confounding the protein concentration in milk. Milk adulterated with melamine can cause acute renal failure, kidneys damage and death. The presence of melamine in milk can be detected using Raman spectroscopy from its unique feature at 676cm -1 Raman shift. In this study, several samples of melamine adulterated milk are prepared in different forms to imitate the possibility on how melamine is illegally added into milk. Using Principal Component Analysis (PCA), dataset of milk and melamine adulterated milk dimension is reduced to several significant principal component which are highly correlated to the melamine and features. The presence of melamine in milk can be visually classified from PCA loading score plots and presented in this paper.