Identification and Quantitation of Melamine in Milk by Near-Infrared Spectroscopy and Chemometrics

Abstract

Melamine is a nitrogen-rich substance and has been illegally used to increase the apparent protein content in food products such as milk. Therefore, it is imperative to develop sensitive and reliable analytical methods to determine melamine in human foods. Current analytical methods for melamine are mainly chromatography-based methods, which are time-consuming and expensive and require complex pretreatment and well-trained technicians. The present paper investigated the feasibility of using near-infrared (NIR) spectroscopy and chemometrics for identifying and quantifying melamine in liquor milk. A total of 75 samples were prepared. Uninformative variable elimination-partial least square (UVE-PLS) and partial least squares-discriminant analysis (PLS-DA) were used to construct quantitative and qualitative models, respectively. Based on the ratio of performance to standard deviate (RPD), UVE-PLS model with 3 components resulted in a better solution. The PLS-DA model achieved an accuracy of 100% and outperformed the optimal reference model of soft independent modeling of class analogy (SIMCA). Such a method can serve as a potential tool for rapid screening of melamine in milk products.