Rapid Detection for Toxicity of Melamine Contamination in Infant formula and Liquid Milk based on Fiber Chemical Sensor

Abstract

Melamine has become as one of the major food adulterants. Therefore in this article, we developed a novel method for detecting the milk contaminants like toxicity of melamine and classified it based on data spectroscopy. The developed system based on optical fiber sensor, Optical spectroscopy and artificial neural network (ANN). The system consists of an optical source, refractive index sensor (RIS), optical detector (photodiode), spectroscopy data and neural package. Where the detection and classification process depends on the read out of the RIS sensor and near-infrared spectroscopies to achieve the detection and recognition of all the samples by using LM-BP neural network algorithm. The classification rate was reported at accuracy rate reach above 99.98%.