Animal fats discrimination using laser induced breakdown spectroscopy and principal component analysis

Abstract

Adulteration of lard in foods raises concerns among Muslims and Jews. To address this issue, laser induced breakdown spectroscopy (LIBS) system is used in this work to differentiate various extracted animal fats in liquid form. However, laser-liquid interaction produces splashing due to the shockwave effect thus generate poor plasma plume in LIBS emission signals. LIBS difficulties in liquid form were overcome by freezing the samples and turned into solid form using freezer and liquid nitrogen. Then, the frozen samples were ablated using Nd:YAG laser of 1064 nm wavelength, 170 mJ pulsed energy and 6 ns pulse duration to produce plasma on sample’s surfaces. The plasma was captured using a spectrometer via optical fiber. The spectrometer was connected to a computer for displaying LIBS signals. The LIBS signals of the samples were then further evaluated using principal component analysis (PCA). PCA is a statistical analysis method for reducing the dimensionality of large data sets without any information loss. Experimental findings indicate that LIBS emission intensity of extracted chicken and lamb fats using liquid nitrogen method was 4 - 37 % and 4 - 19 % higher than freezer method, respectively. However, LIBS emission intensity of extracted beef fat and lard using freezer method was 12 - 41 % and 6 - 59 % higher than liquid nitrogen method, respectively. PCA demonstrated that the data points of extracted animal fats using liquid nitrogen method were more clustered than those frozen in the freezer. PCA also revealed that good discrimination achieved between extracted animal fats using liquid nitrogen method compared to the freezer freezing method. Therefore, LIBS system coupled with the PCA approach has high potential for detection of animal fats in food products.