Investigation of biomarking patterns in fats from various sources for halal authentication using infrared instruments

Abstract

An important issue in food industry is the authenticity of food products. Tampering with the authenticity of food product can involve the alteration of correct labeling of food ingredients, whereby high value raw materials such as cow skin are substituted with cheaper materials such as pig skin.. The verification of labels in any food product is necessary in order to prevent adulteration practices. Authentication techniques for detection of adulteration in meat products is being developed using current technology which enables the food product to be analysed for authenticity. Applications include the effective determination of illegal substances in halal products. Scientists have introduced various halal authentication techniques. Infrared (IR) spectroscopy is a rapid and non-destructive technique, thus allowing the screening of a large number of samples that can be recovered after measurement and used later for further analyses. In this study,there are four types of identification using pig biomarker based on FTIR technique was carried out such as comparing the spectral pattern of fat in FTIR spectrum in pure meat from pig, lamb, cow, chicken, and palm oil, study effect of the cooking and mixing process on the spectral pattern of fat, authenticate food products using the biomarker pattern determined, study modelling experiment to determine significance of different fat using Minitab software. Five fat samples and sixteen wavelenghts were discerned for use as biomarkers. The sixteen wavelenghts identified included four wavelenghts in the functional group region and twelve wavelenghts in the fingerprint region. Prominent peaks in the functional group region were at wavelenghts 3007 nm, 2948.9 nm, 2918 nm and 2850 nm. Twelve prominent wavelengths in fingerprint group were identified: wavelengths 1743.1, 1466, 1416.5, 1377.7, 1236, 1216.3, 1178, 1141, 1116.6, 1098.4, 1082.7 and 965.1. The sixteen wavelengths in the spectrum can be plotted to distinguish pig fat against beef fat, lamb fat, and palm oil, but not pig fat against chicken fat becauses the biomarkers for pig and chicken fats were visually similar. At frequency 1236 and 3007 nm of the score plots. the biomarker wavelengths for pig and chicken fat as well as pig fat and beef fat, lamb fat and palm oil were located significantly far away. Using these two wavelengths for idenfication of all the fats in food samples would sufficiently distinguish between the fats and oil. The score plot for the animal fats processed differently (via oven, baked, fried, and boiled) remains grouped within the same type of animal fat. This suggest that processing did not cause structural changes in the fat derived from the four types of animal meat. Twenty-six fats at two frequencies along the graph (1236 and 3007 nm), indicating Meat Ball B (MBB) fat, Meat Ball A (MBA) fat, and Sausage B (SB) fat samples were able to identify each fat distinctly as there was clear distance between the biomarker points. Using values for points at these two frequencies for identification of the food samples was chosen as biomarkers as they were located distinctly apart from each other. The first two samples, MBB and SB that were located very close to PF indicated that MBB and SB samples contained pork fat; MBA was located close to CF, indicating the possibility that this sample contained chicken fat. Modeling experiment using interaction plot for group, showed a significant difference between CF-LF, BF-CF, BF-PF, LF-PF. The opposite looks very similar is between LF-PO, BF-PO, CF-PF.